Overview

Dataset statistics

Number of variables59
Number of observations56
Missing cells1204
Missing cells (%)36.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.9 KiB
Average record size in memory474.3 B

Variable types

Numeric11
Categorical39
Unsupported9

Alerts

type has constant value "regular" Constant
airdate has constant value "2020-12-05" Constant
url has a high cardinality: 56 distinct values High cardinality
name has a high cardinality: 53 distinct values High cardinality
_links.self.href has a high cardinality: 56 distinct values High cardinality
id is highly correlated with rating.average and 3 other fieldsHigh correlation
season is highly correlated with rating.average and 4 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 4 other fieldsHigh correlation
rating.average is highly correlated with id and 11 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 5 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with runtime and 2 other fieldsHigh correlation
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with runtime and 4 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with season and 4 other fieldsHigh correlation
rating.average is highly correlated with id and 11 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 5 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.webChannel.idHigh correlation
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with rating.average and 3 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 4 other fieldsHigh correlation
rating.average is highly correlated with id and 11 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with runtime and 1 other fieldsHigh correlation
id is highly correlated with url and 33 other fieldsHigh correlation
url is highly correlated with id and 44 other fieldsHigh correlation
name is highly correlated with id and 39 other fieldsHigh correlation
season is highly correlated with url and 26 other fieldsHigh correlation
number is highly correlated with url and 24 other fieldsHigh correlation
airtime is highly correlated with url and 36 other fieldsHigh correlation
airstamp is highly correlated with id and 42 other fieldsHigh correlation
runtime is highly correlated with url and 31 other fieldsHigh correlation
summary is highly correlated with id and 40 other fieldsHigh correlation
_links.self.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.status is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.ended is highly correlated with url and 32 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 20 other fieldsHigh correlation
_embedded.show.weight is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with id and 25 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 30 other fieldsHigh correlation
image.medium is highly correlated with id and 41 other fieldsHigh correlation
image.original is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 37 other fieldsHigh correlation
runtime has 4 (7.1%) missing values Missing
image has 56 (100.0%) missing values Missing
summary has 44 (78.6%) missing values Missing
rating.average has 54 (96.4%) missing values Missing
_embedded.show.runtime has 23 (41.1%) missing values Missing
_embedded.show.averageRuntime has 5 (8.9%) missing values Missing
_embedded.show.ended has 43 (76.8%) missing values Missing
_embedded.show.officialSite has 2 (3.6%) missing values Missing
_embedded.show.rating.average has 51 (91.1%) missing values Missing
_embedded.show.network has 56 (100.0%) missing values Missing
_embedded.show.webChannel.id has 1 (1.8%) missing values Missing
_embedded.show.webChannel.name has 1 (1.8%) missing values Missing
_embedded.show.webChannel.country.name has 19 (33.9%) missing values Missing
_embedded.show.webChannel.country.code has 19 (33.9%) missing values Missing
_embedded.show.webChannel.country.timezone has 19 (33.9%) missing values Missing
_embedded.show.webChannel.officialSite has 35 (62.5%) missing values Missing
_embedded.show.dvdCountry has 56 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 54 (96.4%) missing values Missing
_embedded.show.externals.thetvdb has 23 (41.1%) missing values Missing
_embedded.show.externals.imdb has 25 (44.6%) missing values Missing
_embedded.show.image.medium has 2 (3.6%) missing values Missing
_embedded.show.image.original has 2 (3.6%) missing values Missing
_embedded.show.summary has 2 (3.6%) missing values Missing
_embedded.show._links.nextepisode.href has 51 (91.1%) missing values Missing
image.medium has 39 (69.6%) missing values Missing
image.original has 39 (69.6%) missing values Missing
_embedded.show.image has 56 (100.0%) missing values Missing
_embedded.show.webChannel.country has 56 (100.0%) missing values Missing
_embedded.show.network.id has 51 (91.1%) missing values Missing
_embedded.show.network.name has 51 (91.1%) missing values Missing
_embedded.show.network.country.name has 51 (91.1%) missing values Missing
_embedded.show.network.country.code has 51 (91.1%) missing values Missing
_embedded.show.network.country.timezone has 51 (91.1%) missing values Missing
_embedded.show.network.officialSite has 56 (100.0%) missing values Missing
_embedded.show.webChannel has 56 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.externals.tvrage is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show.network.id is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:37:42.030392
Analysis finished2022-09-06 02:37:57.791052
Duration15.76 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2071036.857
Minimum1943279
Maximum2386104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:37:57.870143image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1943279
5-th percentile1959411.25
Q11973526.75
median2038726.5
Q32153997.25
95-th percentile2305457.25
Maximum2386104
Range442825
Interquartile range (IQR)180470.5

Descriptive statistics

Standard deviation115990.7037
Coefficient of variation (CV)0.05600610307
Kurtosis-0.2168441787
Mean2071036.857
Median Absolute Deviation (MAD)75630.5
Skewness0.8319030251
Sum115978064
Variance1.345384334 × 1010
MonotonicityNot monotonic
2022-09-05T21:37:57.992718image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19798261
 
1.8%
19681121
 
1.8%
19798491
 
1.8%
21302701
 
1.8%
19809541
 
1.8%
20420021
 
1.8%
19802081
 
1.8%
19465811
 
1.8%
19810491
 
1.8%
19659501
 
1.8%
Other values (46)46
82.1%
ValueCountFrequency (%)
19432791
1.8%
19465811
1.8%
19537871
1.8%
19612861
1.8%
19620561
1.8%
19659211
1.8%
19659501
1.8%
19670671
1.8%
19681121
1.8%
19690541
1.8%
ValueCountFrequency (%)
23861041
1.8%
23180971
1.8%
23112121
1.8%
23035391
1.8%
22893201
1.8%
22121651
1.8%
21821161
1.8%
21817951
1.8%
21761221
1.8%
21540021
1.8%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://www.tvmaze.com/episodes/1979826/sim-for-you-4x18-chanyeols-episode-18
 
1
https://www.tvmaze.com/episodes/1968112/po-sezonu-videodajdzest-seasonvar-6x49-vypusk-303
 
1
https://www.tvmaze.com/episodes/1979849/neznyj-redaktor-6x01-cajldfri-ili-rozat-zacem-nuzny-deti-intensivnoe-materinstvo-podrugi
 
1
https://www.tvmaze.com/episodes/2130270/wowcraft-1x52-expac-tations
 
1
https://www.tvmaze.com/episodes/1980954/jachtseizoen-5x06-gaby-blaaser-op-de-vlucht
 
1
Other values (51)
51 

Length

Max length131
Median length91.5
Mean length81.57142857
Min length55

Characters and Unicode

Total characters4568
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1979826/sim-for-you-4x18-chanyeols-episode-18
2nd rowhttps://www.tvmaze.com/episodes/1968112/po-sezonu-videodajdzest-seasonvar-6x49-vypusk-303
3rd rowhttps://www.tvmaze.com/episodes/1980956/soul-land-7x03-di133ji
4th rowhttps://www.tvmaze.com/episodes/2386104/xian-feng-jian-yu-lu-1x45-episode-45
5th rowhttps://www.tvmaze.com/episodes/1962056/heaven-officials-blessing-1x07-scorpion-tailed-snake-shadow

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1979826/sim-for-you-4x18-chanyeols-episode-181
 
1.8%
https://www.tvmaze.com/episodes/1968112/po-sezonu-videodajdzest-seasonvar-6x49-vypusk-3031
 
1.8%
https://www.tvmaze.com/episodes/1979849/neznyj-redaktor-6x01-cajldfri-ili-rozat-zacem-nuzny-deti-intensivnoe-materinstvo-podrugi1
 
1.8%
https://www.tvmaze.com/episodes/2130270/wowcraft-1x52-expac-tations1
 
1.8%
https://www.tvmaze.com/episodes/1980954/jachtseizoen-5x06-gaby-blaaser-op-de-vlucht1
 
1.8%
https://www.tvmaze.com/episodes/2042002/game-changer-wrestling-2020-12-05-gcw-slime-season1
 
1.8%
https://www.tvmaze.com/episodes/1980208/world-war-two-week-by-week-3x14-december-5-19411
 
1.8%
https://www.tvmaze.com/episodes/1946581/detention-1x01-devil1
 
1.8%
https://www.tvmaze.com/episodes/1981049/detention-1x02-who-am-i1
 
1.8%
https://www.tvmaze.com/episodes/1965950/i-told-sunset-about-you-the-documentary-1x08-all-the-significance1
 
1.8%
Other values (46)46
82.1%

Length

2022-09-05T21:37:58.119838image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1979826/sim-for-you-4x18-chanyeols-episode-181
 
1.8%
https://www.tvmaze.com/episodes/1968112/po-sezonu-videodajdzest-seasonvar-6x49-vypusk-3031
 
1.8%
https://www.tvmaze.com/episodes/2041863/fandom-tour-1x12-stray-kidsui-majimag-chueog-yeohaeng1
 
1.8%
https://www.tvmaze.com/episodes/1980956/soul-land-7x03-di133ji1
 
1.8%
https://www.tvmaze.com/episodes/2386104/xian-feng-jian-yu-lu-1x45-episode-451
 
1.8%
https://www.tvmaze.com/episodes/1962056/heaven-officials-blessing-1x07-scorpion-tailed-snake-shadow1
 
1.8%
https://www.tvmaze.com/episodes/1972559/the-wolf-1x17-episode-171
 
1.8%
https://www.tvmaze.com/episodes/1972560/the-wolf-1x18-episode-181
 
1.8%
https://www.tvmaze.com/episodes/2113317/klassen-3x16-bursdagstyven1
 
1.8%
https://www.tvmaze.com/episodes/1969218/team-ingebrigtsen-4x01-episode-11
 
1.8%
Other values (46)46
82.1%

Most occurring characters

ValueCountFrequency (%)
e385
 
8.4%
-357
 
7.8%
s294
 
6.4%
t292
 
6.4%
/280
 
6.1%
o232
 
5.1%
w200
 
4.4%
i189
 
4.1%
a173
 
3.8%
m151
 
3.3%
Other values (30)2015
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3114
68.2%
Decimal Number649
 
14.2%
Other Punctuation448
 
9.8%
Dash Punctuation357
 
7.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e385
12.4%
s294
 
9.4%
t292
 
9.4%
o232
 
7.5%
w200
 
6.4%
i189
 
6.1%
a173
 
5.6%
m151
 
4.8%
p150
 
4.8%
n124
 
4.0%
Other values (16)924
29.7%
Decimal Number
ValueCountFrequency (%)
1145
22.3%
098
15.1%
297
14.9%
970
10.8%
549
 
7.6%
347
 
7.2%
740
 
6.2%
837
 
5.7%
634
 
5.2%
432
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/280
62.5%
.112
 
25.0%
:56
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-357
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3114
68.2%
Common1454
31.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e385
12.4%
s294
 
9.4%
t292
 
9.4%
o232
 
7.5%
w200
 
6.4%
i189
 
6.1%
a173
 
5.6%
m151
 
4.8%
p150
 
4.8%
n124
 
4.0%
Other values (16)924
29.7%
Common
ValueCountFrequency (%)
-357
24.6%
/280
19.3%
1145
10.0%
.112
 
7.7%
098
 
6.7%
297
 
6.7%
970
 
4.8%
:56
 
3.9%
549
 
3.4%
347
 
3.2%
Other values (4)143
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII4568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e385
 
8.4%
-357
 
7.8%
s294
 
6.4%
t292
 
6.4%
/280
 
6.1%
o232
 
5.1%
w200
 
4.4%
i189
 
4.1%
a173
 
3.8%
m151
 
3.3%
Other values (30)2015
44.1%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct53
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size576.0 B
Episode 1
 
2
Episode 2
 
2
Episode 5
 
2
Chanyeol's Episode 18
 
1
Episode 41
 
1
Other values (48)
48 

Length

Max length72
Median length45
Mean length18.69642857
Min length5

Characters and Unicode

Total characters1047
Distinct characters111
Distinct categories8 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)89.3%

Sample

1st rowChanyeol's Episode 18
2nd rowВыпуск 303
3rd row第133集
4th rowEpisode 45
5th rowScorpion-Tailed Snake Shadow

Common Values

ValueCountFrequency (%)
Episode 12
 
3.6%
Episode 22
 
3.6%
Episode 52
 
3.6%
Chanyeol's Episode 181
 
1.8%
Episode 411
 
1.8%
Gaby Blaaser op de vlucht1
 
1.8%
GCW Slime Season1
 
1.8%
December 5, 19411
 
1.8%
Devil1
 
1.8%
Who am I?1
 
1.8%
Other values (43)43
76.8%

Length

2022-09-05T21:37:58.239455image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode11
 
6.0%
the4
 
2.2%
54
 
2.2%
vs3
 
1.6%
3
 
1.6%
on3
 
1.6%
23
 
1.6%
water2
 
1.1%
of2
 
1.1%
og2
 
1.1%
Other values (138)146
79.8%

Most occurring characters

ValueCountFrequency (%)
127
 
12.1%
e75
 
7.2%
i60
 
5.7%
a52
 
5.0%
o50
 
4.8%
s48
 
4.6%
t43
 
4.1%
r42
 
4.0%
n40
 
3.8%
l28
 
2.7%
Other values (101)482
46.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter671
64.1%
Uppercase Letter168
 
16.0%
Space Separator127
 
12.1%
Decimal Number45
 
4.3%
Other Punctuation21
 
2.0%
Other Letter10
 
1.0%
Dash Punctuation3
 
0.3%
Math Symbol2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e75
 
11.2%
i60
 
8.9%
a52
 
7.7%
o50
 
7.5%
s48
 
7.2%
t43
 
6.4%
r42
 
6.3%
n40
 
6.0%
l28
 
4.2%
h26
 
3.9%
Other values (34)207
30.8%
Uppercase Letter
ValueCountFrequency (%)
E19
 
11.3%
S17
 
10.1%
T12
 
7.1%
C12
 
7.1%
B12
 
7.1%
F8
 
4.8%
H7
 
4.2%
P6
 
3.6%
I6
 
3.6%
D6
 
3.6%
Other values (28)63
37.5%
Decimal Number
ValueCountFrequency (%)
112
26.7%
26
13.3%
55
11.1%
35
11.1%
44
 
8.9%
03
 
6.7%
93
 
6.7%
73
 
6.7%
83
 
6.7%
61
 
2.2%
Other Letter
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Other Punctuation
ValueCountFrequency (%)
,6
28.6%
.5
23.8%
?3
14.3%
:3
14.3%
"2
 
9.5%
'2
 
9.5%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin768
73.4%
Common198
 
18.9%
Cyrillic71
 
6.8%
Hangul8
 
0.8%
Han2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e75
 
9.8%
i60
 
7.8%
a52
 
6.8%
o50
 
6.5%
s48
 
6.2%
t43
 
5.6%
r42
 
5.5%
n40
 
5.2%
l28
 
3.6%
h26
 
3.4%
Other values (38)304
39.6%
Cyrillic
ValueCountFrequency (%)
и6
 
8.5%
н6
 
8.5%
е6
 
8.5%
т5
 
7.0%
с4
 
5.6%
а3
 
4.2%
о3
 
4.2%
р3
 
4.2%
И3
 
4.2%
в2
 
2.8%
Other values (24)30
42.3%
Common
ValueCountFrequency (%)
127
64.1%
112
 
6.1%
26
 
3.0%
,6
 
3.0%
55
 
2.5%
.5
 
2.5%
35
 
2.5%
44
 
2.0%
03
 
1.5%
93
 
1.5%
Other values (9)22
 
11.1%
Hangul
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII962
91.9%
Cyrillic71
 
6.8%
Hangul8
 
0.8%
None4
 
0.4%
CJK2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
 
13.2%
e75
 
7.8%
i60
 
6.2%
a52
 
5.4%
o50
 
5.2%
s48
 
5.0%
t43
 
4.5%
r42
 
4.4%
n40
 
4.2%
l28
 
2.9%
Other values (55)397
41.3%
Cyrillic
ValueCountFrequency (%)
и6
 
8.5%
н6
 
8.5%
е6
 
8.5%
т5
 
7.0%
с4
 
5.6%
а3
 
4.2%
о3
 
4.2%
р3
 
4.2%
И3
 
4.2%
в2
 
2.8%
Other values (24)30
42.3%
None
ValueCountFrequency (%)
å2
50.0%
ø2
50.0%
Hangul
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290.4285714
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:37:58.327205image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q35.25
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation712.4871127
Coefficient of variation (CV)2.453226655
Kurtosis2.488575167
Mean290.4285714
Median Absolute Deviation (MAD)0
Skewness2.097827726
Sum16264
Variance507637.8857
MonotonicityNot monotonic
2022-09-05T21:37:58.416998image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
132
57.1%
20208
 
14.3%
43
 
5.4%
63
 
5.4%
33
 
5.4%
23
 
5.4%
72
 
3.6%
51
 
1.8%
81
 
1.8%
ValueCountFrequency (%)
132
57.1%
23
 
5.4%
33
 
5.4%
43
 
5.4%
51
 
1.8%
63
 
5.4%
72
 
3.6%
81
 
1.8%
20208
 
14.3%
ValueCountFrequency (%)
20208
 
14.3%
81
 
1.8%
72
 
3.6%
63
 
5.4%
51
 
1.8%
43
 
5.4%
33
 
5.4%
23
 
5.4%
132
57.1%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct26
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.78571429
Minimum1
Maximum332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:37:58.505076image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.75
median7
Q316
95-th percentile51.25
Maximum332
Range331
Interquartile range (IQR)12.25

Descriptive statistics

Standard deviation45.5937453
Coefficient of variation (CV)2.427043476
Kurtosis42.1024161
Mean18.78571429
Median Absolute Deviation (MAD)4.5
Skewness6.171447763
Sum1052
Variance2078.78961
MonotonicityNot monotonic
2022-09-05T21:37:58.602742image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
35
 
8.9%
15
 
8.9%
54
 
7.1%
24
 
7.1%
44
 
7.1%
64
 
7.1%
103
 
5.4%
83
 
5.4%
183
 
5.4%
73
 
5.4%
Other values (16)18
32.1%
ValueCountFrequency (%)
15
8.9%
24
7.1%
35
8.9%
44
7.1%
54
7.1%
64
7.1%
73
5.4%
83
5.4%
91
 
1.8%
103
5.4%
ValueCountFrequency (%)
3321
 
1.8%
841
 
1.8%
521
 
1.8%
511
 
1.8%
491
 
1.8%
451
 
1.8%
411
 
1.8%
292
3.6%
183
5.4%
171
 
1.8%

type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size576.0 B
regular
56 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters392
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular56
100.0%

Length

2022-09-05T21:37:58.686638image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:58.760566image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular56
100.0%

Most occurring characters

ValueCountFrequency (%)
r112
28.6%
e56
14.3%
g56
14.3%
u56
14.3%
l56
14.3%
a56
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter392
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r112
28.6%
e56
14.3%
g56
14.3%
u56
14.3%
l56
14.3%
a56
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin392
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r112
28.6%
e56
14.3%
g56
14.3%
u56
14.3%
l56
14.3%
a56
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r112
28.6%
e56
14.3%
g56
14.3%
u56
14.3%
l56
14.3%
a56
14.3%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size576.0 B
2020-12-05
56 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters560
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-05
2nd row2020-12-05
3rd row2020-12-05
4th row2020-12-05
5th row2020-12-05

Common Values

ValueCountFrequency (%)
2020-12-0556
100.0%

Length

2022-09-05T21:37:58.826214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:58.899642image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-0556
100.0%

Most occurring characters

ValueCountFrequency (%)
2168
30.0%
0168
30.0%
-112
20.0%
156
 
10.0%
556
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number448
80.0%
Dash Punctuation112
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2168
37.5%
0168
37.5%
156
 
12.5%
556
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common560
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2168
30.0%
0168
30.0%
-112
20.0%
156
 
10.0%
556
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2168
30.0%
0168
30.0%
-112
20.0%
156
 
10.0%
556
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct16
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size576.0 B
34 
06:00
10:00
 
2
11:00
 
2
18:00
 
2
Other values (11)
11 

Length

Max length5
Median length0
Mean length1.964285714
Min length0

Characters and Unicode

Total characters110
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)19.6%

Sample

1st row06:00
2nd row
3rd row10:00
4th row10:00
5th row11:00

Common Values

ValueCountFrequency (%)
34
60.7%
06:005
 
8.9%
10:002
 
3.6%
11:002
 
3.6%
18:002
 
3.6%
05:001
 
1.8%
17:001
 
1.8%
18:301
 
1.8%
20:001
 
1.8%
00:001
 
1.8%
Other values (6)6
 
10.7%

Length

2022-09-05T21:37:58.973550image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06:005
22.7%
10:002
 
9.1%
11:002
 
9.1%
18:002
 
9.1%
05:001
 
4.5%
17:001
 
4.5%
18:301
 
4.5%
20:001
 
4.5%
00:001
 
4.5%
00:151
 
4.5%
Other values (5)5
22.7%

Most occurring characters

ValueCountFrequency (%)
050
45.5%
:22
20.0%
115
 
13.6%
66
 
5.5%
55
 
4.5%
24
 
3.6%
83
 
2.7%
32
 
1.8%
92
 
1.8%
71
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number88
80.0%
Other Punctuation22
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
050
56.8%
115
 
17.0%
66
 
6.8%
55
 
5.7%
24
 
4.5%
83
 
3.4%
32
 
2.3%
92
 
2.3%
71
 
1.1%
Other Punctuation
ValueCountFrequency (%)
:22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
050
45.5%
:22
20.0%
115
 
13.6%
66
 
5.5%
55
 
4.5%
24
 
3.6%
83
 
2.7%
32
 
1.8%
92
 
1.8%
71
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
050
45.5%
:22
20.0%
115
 
13.6%
66
 
5.5%
55
 
4.5%
24
 
3.6%
83
 
2.7%
32
 
1.8%
92
 
1.8%
71
 
0.9%

airstamp
Categorical

HIGH CORRELATION

Distinct23
Distinct (%)41.1%
Missing0
Missing (%)0.0%
Memory size576.0 B
2020-12-05T12:00:00+00:00
15 
2020-12-05T11:00:00+00:00
11 
2020-12-05T17:00:00+00:00
2020-12-05T04:00:00+00:00
2020-12-05T05:00:00+00:00
Other values (18)
20 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1400
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)28.6%

Sample

1st row2020-12-04T21:00:00+00:00
2nd row2020-12-05T00:00:00+00:00
3rd row2020-12-05T02:00:00+00:00
4th row2020-12-05T02:00:00+00:00
5th row2020-12-05T03:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-05T12:00:00+00:0015
26.8%
2020-12-05T11:00:00+00:0011
19.6%
2020-12-05T17:00:00+00:004
 
7.1%
2020-12-05T04:00:00+00:003
 
5.4%
2020-12-05T05:00:00+00:003
 
5.4%
2020-12-05T02:00:00+00:002
 
3.6%
2020-12-05T09:00:00+00:002
 
3.6%
2020-12-05T15:00:00+00:001
 
1.8%
2020-12-06T00:30:00+00:001
 
1.8%
2020-12-05T21:00:00+00:001
 
1.8%
Other values (13)13
23.2%

Length

2022-09-05T21:37:59.078155image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-05t12:00:00+00:0015
26.8%
2020-12-05t11:00:00+00:0011
19.6%
2020-12-05t17:00:00+00:004
 
7.1%
2020-12-05t04:00:00+00:003
 
5.4%
2020-12-05t05:00:00+00:003
 
5.4%
2020-12-05t02:00:00+00:002
 
3.6%
2020-12-05t09:00:00+00:002
 
3.6%
2020-12-05t13:00:00+00:001
 
1.8%
2020-12-05t03:00:00+00:001
 
1.8%
2020-12-05t06:00:00+00:001
 
1.8%
Other values (13)13
23.2%

Most occurring characters

ValueCountFrequency (%)
0630
45.0%
2188
 
13.4%
:168
 
12.0%
-112
 
8.0%
1105
 
7.5%
562
 
4.4%
T56
 
4.0%
+56
 
4.0%
75
 
0.4%
35
 
0.4%
Other values (4)13
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1008
72.0%
Other Punctuation168
 
12.0%
Dash Punctuation112
 
8.0%
Uppercase Letter56
 
4.0%
Math Symbol56
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0630
62.5%
2188
 
18.7%
1105
 
10.4%
562
 
6.2%
75
 
0.5%
35
 
0.5%
44
 
0.4%
64
 
0.4%
93
 
0.3%
82
 
0.2%
Other Punctuation
ValueCountFrequency (%)
:168
100.0%
Dash Punctuation
ValueCountFrequency (%)
-112
100.0%
Uppercase Letter
ValueCountFrequency (%)
T56
100.0%
Math Symbol
ValueCountFrequency (%)
+56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1344
96.0%
Latin56
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0630
46.9%
2188
 
14.0%
:168
 
12.5%
-112
 
8.3%
1105
 
7.8%
562
 
4.6%
+56
 
4.2%
75
 
0.4%
35
 
0.4%
44
 
0.3%
Other values (3)9
 
0.7%
Latin
ValueCountFrequency (%)
T56
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0630
45.0%
2188
 
13.4%
:168
 
12.0%
-112
 
8.0%
1105
 
7.5%
562
 
4.4%
T56
 
4.0%
+56
 
4.0%
75
 
0.4%
35
 
0.4%
Other values (4)13
 
0.9%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct24
Distinct (%)46.2%
Missing4
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean40.67307692
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:37:59.165387image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q17.25
median23
Q345.5
95-th percentile120
Maximum300
Range298
Interquartile range (IQR)38.25

Descriptive statistics

Standard deviation58.94454727
Coefficient of variation (CV)1.44922764
Kurtosis12.70735394
Mean40.67307692
Median Absolute Deviation (MAD)18
Skewness3.382675849
Sum2115
Variance3474.459653
MonotonicityNot monotonic
2022-09-05T21:37:59.257556image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
511
19.6%
305
 
8.9%
454
 
7.1%
203
 
5.4%
603
 
5.4%
162
 
3.6%
212
 
3.6%
1202
 
3.6%
82
 
3.6%
152
 
3.6%
Other values (14)16
28.6%
(Missing)4
 
7.1%
ValueCountFrequency (%)
21
 
1.8%
41
 
1.8%
511
19.6%
82
 
3.6%
111
 
1.8%
152
 
3.6%
162
 
3.6%
203
 
5.4%
212
 
3.6%
232
 
3.6%
ValueCountFrequency (%)
3001
 
1.8%
2931
 
1.8%
1202
3.6%
931
 
1.8%
911
 
1.8%
611
 
1.8%
603
5.4%
561
 
1.8%
521
 
1.8%
471
 
1.8%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct12
Distinct (%)100.0%
Missing44
Missing (%)78.6%
Memory size576.0 B
<p><b>#DangerQuest #AbleToFly(?) #EntranceOfAWindSkill</b></p>
<p>The Wehrmacht is halted by the Red Army at the gates of Moscow. Not only that, but a Red Army counteroffensive begins pushing the Germans back decisively. The Germans are also beginning to withdraw from their siege of Tobruk in North Africa. Japan, however, is advancing all over the Pacific, sending troop transports into the South China Sea, though it is unclear just whom Japan plans to attack. The Japanese are also- in top secrecy- sending a force of aircraft carriers to soon attack the American Pacific fleet at anchor at Pearl Harbor.</p>
<p>At Greenwood High School, transfer student Liu Yun-hsiang witnesses a shocking incident at a deserted building and runs afoul of school authorities.</p><p><br /> </p>
<p>After an initial encounter with Fang Jui-hsin's spirit, Yun-hsiang finds herself in an otherworldly dimension and accepts a life-altering bargain.</p>
<p>Go behind the scenes with Billkin and PP as the reflect on the intimate moments in the show.  The crew also reveal some of the difficult scenes to film involving road closures and other challenges. </p>
Other values (7)

Length

Max length549
Median length171
Mean length192.9166667
Min length62

Characters and Unicode

Total characters2315
Distinct characters63
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row<p><b>#DangerQuest #AbleToFly(?) #EntranceOfAWindSkill</b></p>
2nd row<p>The Wehrmacht is halted by the Red Army at the gates of Moscow. Not only that, but a Red Army counteroffensive begins pushing the Germans back decisively. The Germans are also beginning to withdraw from their siege of Tobruk in North Africa. Japan, however, is advancing all over the Pacific, sending troop transports into the South China Sea, though it is unclear just whom Japan plans to attack. The Japanese are also- in top secrecy- sending a force of aircraft carriers to soon attack the American Pacific fleet at anchor at Pearl Harbor.</p>
3rd row<p>At Greenwood High School, transfer student Liu Yun-hsiang witnesses a shocking incident at a deserted building and runs afoul of school authorities.</p><p><br /> </p>
4th row<p>After an initial encounter with Fang Jui-hsin's spirit, Yun-hsiang finds herself in an otherworldly dimension and accepts a life-altering bargain.</p>
5th row<p>Go behind the scenes with Billkin and PP as the reflect on the intimate moments in the show.  The crew also reveal some of the difficult scenes to film involving road closures and other challenges. </p>

Common Values

ValueCountFrequency (%)
<p><b>#DangerQuest #AbleToFly(?) #EntranceOfAWindSkill</b></p>1
 
1.8%
<p>The Wehrmacht is halted by the Red Army at the gates of Moscow. Not only that, but a Red Army counteroffensive begins pushing the Germans back decisively. The Germans are also beginning to withdraw from their siege of Tobruk in North Africa. Japan, however, is advancing all over the Pacific, sending troop transports into the South China Sea, though it is unclear just whom Japan plans to attack. The Japanese are also- in top secrecy- sending a force of aircraft carriers to soon attack the American Pacific fleet at anchor at Pearl Harbor.</p>1
 
1.8%
<p>At Greenwood High School, transfer student Liu Yun-hsiang witnesses a shocking incident at a deserted building and runs afoul of school authorities.</p><p><br /> </p>1
 
1.8%
<p>After an initial encounter with Fang Jui-hsin's spirit, Yun-hsiang finds herself in an otherworldly dimension and accepts a life-altering bargain.</p>1
 
1.8%
<p>Go behind the scenes with Billkin and PP as the reflect on the intimate moments in the show.  The crew also reveal some of the difficult scenes to film involving road closures and other challenges. </p>1
 
1.8%
<p>Supermom Tregaye Fraser throws the ultimate birthday party for Zaire with a Slider and Brat Bar, a Quick Chili for the hot dogs and a tasty Pimento Cheese. For dessert, indulge in delicious Peanut Butter and Strawberry Shortcake Jars.</p>1
 
1.8%
<p>Off and Boat, explore an abandoned four-story building. Off realizes that there is something even scarier.</p>1
 
1.8%
<p>This is an original story not from the book. The keyword in the story is "a meeting over time".</p>1
 
1.8%
<p>This is it. Their chance to tell the world the truth. Will their message be heard?</p>1
 
1.8%
<p>Chef Lovely plans the ultimate cookout with her Signature Burger, Mama's Potato Salad, Eberhart Street Corn with a Creamy Avocado Drizzle and Grilled Pound Cake with Cherries and Mascarpone. Plus, there's a Cherry Tarragon Limeade to wash it all down!</p>1
 
1.8%
Other values (2)2
 
3.6%
(Missing)44
78.6%

Length

2022-09-05T21:37:59.349858image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the26
 
7.1%
and11
 
3.0%
a11
 
3.0%
to10
 
2.7%
is8
 
2.2%
with7
 
1.9%
in6
 
1.6%
of6
 
1.6%
an5
 
1.4%
at4
 
1.1%
Other values (233)272
74.3%

Most occurring characters

ValueCountFrequency (%)
351
15.2%
e197
 
8.5%
t156
 
6.7%
a155
 
6.7%
i139
 
6.0%
r136
 
5.9%
n119
 
5.1%
o118
 
5.1%
s108
 
4.7%
h94
 
4.1%
Other values (53)742
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1713
74.0%
Space Separator355
 
15.3%
Uppercase Letter113
 
4.9%
Other Punctuation66
 
2.9%
Math Symbol58
 
2.5%
Dash Punctuation8
 
0.3%
Close Punctuation1
 
< 0.1%
Open Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e197
11.5%
t156
 
9.1%
a155
 
9.0%
i139
 
8.1%
r136
 
7.9%
n119
 
6.9%
o118
 
6.9%
s108
 
6.3%
h94
 
5.5%
l68
 
4.0%
Other values (15)423
24.7%
Uppercase Letter
ValueCountFrequency (%)
T15
13.3%
C11
 
9.7%
P11
 
9.7%
S11
 
9.7%
A9
 
8.0%
B8
 
7.1%
J6
 
5.3%
G5
 
4.4%
L5
 
4.4%
O4
 
3.5%
Other values (13)28
24.8%
Other Punctuation
ValueCountFrequency (%)
.22
33.3%
,17
25.8%
/15
22.7%
'4
 
6.1%
#3
 
4.5%
"2
 
3.0%
?2
 
3.0%
!1
 
1.5%
Space Separator
ValueCountFrequency (%)
351
98.9%
 4
 
1.1%
Math Symbol
ValueCountFrequency (%)
<29
50.0%
>29
50.0%
Dash Punctuation
ValueCountFrequency (%)
-8
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1826
78.9%
Common489
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e197
 
10.8%
t156
 
8.5%
a155
 
8.5%
i139
 
7.6%
r136
 
7.4%
n119
 
6.5%
o118
 
6.5%
s108
 
5.9%
h94
 
5.1%
l68
 
3.7%
Other values (38)536
29.4%
Common
ValueCountFrequency (%)
351
71.8%
<29
 
5.9%
>29
 
5.9%
.22
 
4.5%
,17
 
3.5%
/15
 
3.1%
-8
 
1.6%
 4
 
0.8%
'4
 
0.8%
#3
 
0.6%
Other values (5)7
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII2311
99.8%
None4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
351
15.2%
e197
 
8.5%
t156
 
6.8%
a155
 
6.7%
i139
 
6.0%
r136
 
5.9%
n119
 
5.1%
o118
 
5.1%
s108
 
4.7%
h94
 
4.1%
Other values (52)738
31.9%
None
ValueCountFrequency (%)
 4
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing54
Missing (%)96.4%
Memory size576.0 B
6.3
8.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row6.3
2nd row8.0

Common Values

ValueCountFrequency (%)
6.31
 
1.8%
8.01
 
1.8%
(Missing)54
96.4%

Length

2022-09-05T21:37:59.435898image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:37:59.521826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
6.31
50.0%
8.01
50.0%

Most occurring characters

ValueCountFrequency (%)
.2
33.3%
61
16.7%
31
16.7%
81
16.7%
01
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number4
66.7%
Other Punctuation2
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
61
25.0%
31
25.0%
81
25.0%
01
25.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.2
33.3%
61
16.7%
31
16.7%
81
16.7%
01
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.2
33.3%
61
16.7%
31
16.7%
81
16.7%
01
16.7%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://api.tvmaze.com/episodes/1979826
 
1
https://api.tvmaze.com/episodes/1968112
 
1
https://api.tvmaze.com/episodes/1979849
 
1
https://api.tvmaze.com/episodes/2130270
 
1
https://api.tvmaze.com/episodes/1980954
 
1
Other values (51)
51 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2184
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1979826
2nd rowhttps://api.tvmaze.com/episodes/1968112
3rd rowhttps://api.tvmaze.com/episodes/1980956
4th rowhttps://api.tvmaze.com/episodes/2386104
5th rowhttps://api.tvmaze.com/episodes/1962056

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19798261
 
1.8%
https://api.tvmaze.com/episodes/19681121
 
1.8%
https://api.tvmaze.com/episodes/19798491
 
1.8%
https://api.tvmaze.com/episodes/21302701
 
1.8%
https://api.tvmaze.com/episodes/19809541
 
1.8%
https://api.tvmaze.com/episodes/20420021
 
1.8%
https://api.tvmaze.com/episodes/19802081
 
1.8%
https://api.tvmaze.com/episodes/19465811
 
1.8%
https://api.tvmaze.com/episodes/19810491
 
1.8%
https://api.tvmaze.com/episodes/19659501
 
1.8%
Other values (46)46
82.1%

Length

2022-09-05T21:37:59.594682image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19798261
 
1.8%
https://api.tvmaze.com/episodes/19681121
 
1.8%
https://api.tvmaze.com/episodes/20418631
 
1.8%
https://api.tvmaze.com/episodes/19809561
 
1.8%
https://api.tvmaze.com/episodes/23861041
 
1.8%
https://api.tvmaze.com/episodes/19620561
 
1.8%
https://api.tvmaze.com/episodes/19725591
 
1.8%
https://api.tvmaze.com/episodes/19725601
 
1.8%
https://api.tvmaze.com/episodes/21133171
 
1.8%
https://api.tvmaze.com/episodes/19692181
 
1.8%
Other values (46)46
82.1%

Most occurring characters

ValueCountFrequency (%)
/224
 
10.3%
p168
 
7.7%
s168
 
7.7%
e168
 
7.7%
t168
 
7.7%
a112
 
5.1%
i112
 
5.1%
.112
 
5.1%
m112
 
5.1%
o112
 
5.1%
Other values (16)728
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1400
64.1%
Other Punctuation392
 
17.9%
Decimal Number392
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p168
12.0%
s168
12.0%
e168
12.0%
t168
12.0%
a112
8.0%
i112
8.0%
m112
8.0%
o112
8.0%
h56
 
4.0%
d56
 
4.0%
Other values (3)168
12.0%
Decimal Number
ValueCountFrequency (%)
174
18.9%
965
16.6%
256
14.3%
034
8.7%
333
8.4%
731
7.9%
529
 
7.4%
827
 
6.9%
625
 
6.4%
418
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/224
57.1%
.112
28.6%
:56
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1400
64.1%
Common784
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/224
28.6%
.112
14.3%
174
 
9.4%
965
 
8.3%
256
 
7.1%
:56
 
7.1%
034
 
4.3%
333
 
4.2%
731
 
4.0%
529
 
3.7%
Other values (3)70
 
8.9%
Latin
ValueCountFrequency (%)
p168
12.0%
s168
12.0%
e168
12.0%
t168
12.0%
a112
8.0%
i112
8.0%
m112
8.0%
o112
8.0%
h56
 
4.0%
d56
 
4.0%
Other values (3)168
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/224
 
10.3%
p168
 
7.7%
s168
 
7.7%
e168
 
7.7%
t168
 
7.7%
a112
 
5.1%
i112
 
5.1%
.112
 
5.1%
m112
 
5.1%
o112
 
5.1%
Other values (16)728
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct44
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46019.39286
Minimum1596
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:37:59.688572image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1596
5-th percentile7409.5
Q140230.25
median51219.5
Q357032
95-th percentile60962.75
Maximum61755
Range60159
Interquartile range (IQR)16801.75

Descriptive statistics

Standard deviation15265.0851
Coefficient of variation (CV)0.3317098327
Kurtosis1.7502184
Mean46019.39286
Median Absolute Deviation (MAD)5812.5
Skewness-1.542065502
Sum2577086
Variance233022823.2
MonotonicityNot monotonic
2022-09-05T21:37:59.798526image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
5703210
 
17.9%
479122
 
3.6%
318942
 
3.6%
511252
 
3.6%
416481
 
1.8%
615361
 
1.8%
538511
 
1.8%
560671
 
1.8%
579451
 
1.8%
608481
 
1.8%
Other values (34)34
60.7%
ValueCountFrequency (%)
15961
1.8%
40911
1.8%
60971
1.8%
78471
1.8%
196671
1.8%
249631
1.8%
252941
1.8%
306061
1.8%
318942
3.6%
336911
1.8%
ValueCountFrequency (%)
617551
 
1.8%
615361
 
1.8%
613071
 
1.8%
608481
 
1.8%
588441
 
1.8%
579561
 
1.8%
579451
 
1.8%
5703210
17.9%
566051
 
1.8%
560671
 
1.8%

_embedded.show.url
Categorical

HIGH CORRELATION

Distinct44
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://www.tvmaze.com/shows/57032/oteren-svenn
10 
https://www.tvmaze.com/shows/47912/the-wolf
 
2
https://www.tvmaze.com/shows/31894/team-ingebrigtsen
 
2
https://www.tvmaze.com/shows/51125/detention
 
2
https://www.tvmaze.com/shows/41648/sim-for-you
 
1
Other values (39)
39 

Length

Max length74
Median length62
Mean length51.125
Min length38

Characters and Unicode

Total characters2863
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)71.4%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvar
3rd rowhttps://www.tvmaze.com/shows/35551/soul-land
4th rowhttps://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu
5th rowhttps://www.tvmaze.com/shows/51670/heaven-officials-blessing

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/57032/oteren-svenn10
 
17.9%
https://www.tvmaze.com/shows/47912/the-wolf2
 
3.6%
https://www.tvmaze.com/shows/31894/team-ingebrigtsen2
 
3.6%
https://www.tvmaze.com/shows/51125/detention2
 
3.6%
https://www.tvmaze.com/shows/41648/sim-for-you1
 
1.8%
https://www.tvmaze.com/shows/61536/ano-ko-no-yume-wo-mitan-desu1
 
1.8%
https://www.tvmaze.com/shows/53851/tregayes-way-in-the-kitchen1
 
1.8%
https://www.tvmaze.com/shows/56067/yaar-jigree-kasooti-degree1
 
1.8%
https://www.tvmaze.com/shows/57945/i-like-to-watch1
 
1.8%
https://www.tvmaze.com/shows/60848/blippi1
 
1.8%
Other values (34)34
60.7%

Length

2022-09-05T21:37:59.909095image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/57032/oteren-svenn10
 
17.9%
https://www.tvmaze.com/shows/51125/detention2
 
3.6%
https://www.tvmaze.com/shows/47912/the-wolf2
 
3.6%
https://www.tvmaze.com/shows/31894/team-ingebrigtsen2
 
3.6%
https://www.tvmaze.com/shows/40232/jachtseizoen1
 
1.8%
https://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvar1
 
1.8%
https://www.tvmaze.com/shows/35551/soul-land1
 
1.8%
https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu1
 
1.8%
https://www.tvmaze.com/shows/51670/heaven-officials-blessing1
 
1.8%
https://www.tvmaze.com/shows/55919/klassen1
 
1.8%
Other values (34)34
60.7%

Most occurring characters

ValueCountFrequency (%)
/280
 
9.8%
w245
 
8.6%
t232
 
8.1%
s225
 
7.9%
o171
 
6.0%
e170
 
5.9%
h131
 
4.6%
m131
 
4.6%
.112
 
3.9%
a106
 
3.7%
Other values (30)1060
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2033
71.0%
Other Punctuation448
 
15.6%
Decimal Number280
 
9.8%
Dash Punctuation102
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w245
12.1%
t232
11.4%
s225
11.1%
o171
 
8.4%
e170
 
8.4%
h131
 
6.4%
m131
 
6.4%
a106
 
5.2%
v74
 
3.6%
n73
 
3.6%
Other values (16)475
23.4%
Decimal Number
ValueCountFrequency (%)
548
17.1%
332
11.4%
030
10.7%
229
10.4%
427
9.6%
127
9.6%
725
8.9%
624
8.6%
921
7.5%
817
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/280
62.5%
.112
 
25.0%
:56
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2033
71.0%
Common830
29.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w245
12.1%
t232
11.4%
s225
11.1%
o171
 
8.4%
e170
 
8.4%
h131
 
6.4%
m131
 
6.4%
a106
 
5.2%
v74
 
3.6%
n73
 
3.6%
Other values (16)475
23.4%
Common
ValueCountFrequency (%)
/280
33.7%
.112
 
13.5%
-102
 
12.3%
:56
 
6.7%
548
 
5.8%
332
 
3.9%
030
 
3.6%
229
 
3.5%
427
 
3.3%
127
 
3.3%
Other values (4)87
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2863
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/280
 
9.8%
w245
 
8.6%
t232
 
8.1%
s225
 
7.9%
o171
 
6.0%
e170
 
5.9%
h131
 
4.6%
m131
 
4.6%
.112
 
3.9%
a106
 
3.7%
Other values (30)1060
37.0%

_embedded.show.name
Categorical

HIGH CORRELATION

Distinct44
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size576.0 B
Oteren Svenn
10 
The Wolf
 
2
Team Ingebrigtsen
 
2
Detention
 
2
Sim for You
 
1
Other values (39)
39 

Length

Max length39
Median length28
Mean length16.375
Min length4

Characters and Unicode

Total characters917
Distinct characters79
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)71.4%

Sample

1st rowSim for You
2nd rowПо сезону. Видеодайджест Seasonvar
3rd rowSoul Land
4th rowXian Feng Jian Yu Lu
5th rowHeaven Official's Blessing

Common Values

ValueCountFrequency (%)
Oteren Svenn10
 
17.9%
The Wolf2
 
3.6%
Team Ingebrigtsen2
 
3.6%
Detention2
 
3.6%
Sim for You1
 
1.8%
Ano ko no Yume wo Mitan Desu1
 
1.8%
Tregaye's Way in the Kitchen1
 
1.8%
Yaar Jigree Kasooti Degree1
 
1.8%
I Like to Watch1
 
1.8%
Blippi1
 
1.8%
Other values (34)34
60.7%

Length

2022-09-05T21:38:00.017448image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
oteren10
 
6.3%
svenn10
 
6.3%
the5
 
3.2%
i2
 
1.3%
week2
 
1.3%
by2
 
1.3%
lovely2
 
1.3%
fight2
 
1.3%
ufc2
 
1.3%
of2
 
1.3%
Other values (112)119
75.3%

Most occurring characters

ValueCountFrequency (%)
e104
 
11.3%
102
 
11.1%
n68
 
7.4%
t48
 
5.2%
i47
 
5.1%
r44
 
4.8%
a43
 
4.7%
o40
 
4.4%
s33
 
3.6%
l23
 
2.5%
Other values (69)365
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter651
71.0%
Uppercase Letter150
 
16.4%
Space Separator102
 
11.1%
Other Punctuation10
 
1.1%
Decimal Number4
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e104
16.0%
n68
 
10.4%
t48
 
7.4%
i47
 
7.2%
r44
 
6.8%
a43
 
6.6%
o40
 
6.1%
s33
 
5.1%
l23
 
3.5%
v17
 
2.6%
Other values (35)184
28.3%
Uppercase Letter
ValueCountFrequency (%)
S22
14.7%
W14
 
9.3%
T13
 
8.7%
O13
 
8.7%
D8
 
5.3%
B8
 
5.3%
F7
 
4.7%
C7
 
4.7%
I6
 
4.0%
Y6
 
4.0%
Other values (17)46
30.7%
Other Punctuation
ValueCountFrequency (%)
.4
40.0%
'4
40.0%
:1
 
10.0%
?1
 
10.0%
Decimal Number
ValueCountFrequency (%)
02
50.0%
22
50.0%
Space Separator
ValueCountFrequency (%)
102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin759
82.8%
Common116
 
12.6%
Cyrillic42
 
4.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e104
 
13.7%
n68
 
9.0%
t48
 
6.3%
i47
 
6.2%
r44
 
5.8%
a43
 
5.7%
o40
 
5.3%
s33
 
4.3%
l23
 
3.0%
S22
 
2.9%
Other values (41)287
37.8%
Cyrillic
ValueCountFrequency (%)
е6
14.3%
о5
11.9%
д4
 
9.5%
т3
 
7.1%
р2
 
4.8%
ж2
 
4.8%
й2
 
4.8%
а2
 
4.8%
ы2
 
4.8%
н2
 
4.8%
Other values (11)12
28.6%
Common
ValueCountFrequency (%)
102
87.9%
.4
 
3.4%
'4
 
3.4%
02
 
1.7%
22
 
1.7%
:1
 
0.9%
?1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII873
95.2%
Cyrillic42
 
4.6%
None2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e104
 
11.9%
102
 
11.7%
n68
 
7.8%
t48
 
5.5%
i47
 
5.4%
r44
 
5.0%
a43
 
4.9%
o40
 
4.6%
s33
 
3.8%
l23
 
2.6%
Other values (46)321
36.8%
Cyrillic
ValueCountFrequency (%)
е6
14.3%
о5
11.9%
д4
 
9.5%
т3
 
7.1%
р2
 
4.8%
ж2
 
4.8%
й2
 
4.8%
а2
 
4.8%
ы2
 
4.8%
н2
 
4.8%
Other values (11)12
28.6%
None
ValueCountFrequency (%)
å1
50.0%
ø1
50.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size576.0 B
Documentary
17 
Scripted
15 
Animation
Talk Show
Reality
Other values (4)

Length

Max length11
Median length10
Mean length8.928571429
Min length6

Characters and Unicode

Total characters500
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.6%

Sample

1st rowReality
2nd rowTalk Show
3rd rowAnimation
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Documentary17
30.4%
Scripted15
26.8%
Animation7
12.5%
Talk Show5
 
8.9%
Reality4
 
7.1%
Sports4
 
7.1%
Variety2
 
3.6%
Award Show1
 
1.8%
Game Show1
 
1.8%

Length

2022-09-05T21:38:00.112340image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:00.211553image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
documentary17
27.0%
scripted15
23.8%
animation7
11.1%
show7
11.1%
talk5
 
7.9%
reality4
 
6.3%
sports4
 
6.3%
variety2
 
3.2%
award1
 
1.6%
game1
 
1.6%

Most occurring characters

ValueCountFrequency (%)
t49
 
9.8%
e39
 
7.8%
r39
 
7.8%
a37
 
7.4%
i35
 
7.0%
o35
 
7.0%
c32
 
6.4%
n31
 
6.2%
S26
 
5.2%
m25
 
5.0%
Other values (16)152
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter430
86.0%
Uppercase Letter63
 
12.6%
Space Separator7
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t49
11.4%
e39
9.1%
r39
9.1%
a37
8.6%
i35
8.1%
o35
8.1%
c32
 
7.4%
n31
 
7.2%
m25
 
5.8%
y23
 
5.3%
Other values (8)85
19.8%
Uppercase Letter
ValueCountFrequency (%)
S26
41.3%
D17
27.0%
A8
 
12.7%
T5
 
7.9%
R4
 
6.3%
V2
 
3.2%
G1
 
1.6%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin493
98.6%
Common7
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t49
 
9.9%
e39
 
7.9%
r39
 
7.9%
a37
 
7.5%
i35
 
7.1%
o35
 
7.1%
c32
 
6.5%
n31
 
6.3%
S26
 
5.3%
m25
 
5.1%
Other values (15)145
29.4%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t49
 
9.8%
e39
 
7.8%
r39
 
7.8%
a37
 
7.4%
i35
 
7.0%
o35
 
7.0%
c32
 
6.4%
n31
 
6.2%
S26
 
5.2%
m25
 
5.0%
Other values (16)152
30.4%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size576.0 B
Norwegian
17 
English
16 
Chinese
Korean
Japanese
Other values (5)

Length

Max length9
Median length8
Mean length7.446428571
Min length4

Characters and Unicode

Total characters417
Distinct characters27
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.4%

Sample

1st rowKorean
2nd rowRussian
3rd rowChinese
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
Norwegian17
30.4%
English16
28.6%
Chinese7
12.5%
Korean4
 
7.1%
Japanese4
 
7.1%
Russian3
 
5.4%
Thai2
 
3.6%
Dutch1
 
1.8%
Panjabi1
 
1.8%
Arabic1
 
1.8%

Length

2022-09-05T21:38:00.302161image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:00.405121image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
norwegian17
30.4%
english16
28.6%
chinese7
12.5%
korean4
 
7.1%
japanese4
 
7.1%
russian3
 
5.4%
thai2
 
3.6%
dutch1
 
1.8%
panjabi1
 
1.8%
arabic1
 
1.8%

Most occurring characters

ValueCountFrequency (%)
n52
12.5%
i47
11.3%
e43
10.3%
a37
8.9%
g33
 
7.9%
s33
 
7.9%
h26
 
6.2%
r22
 
5.3%
o21
 
5.0%
N17
 
4.1%
Other values (17)86
20.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter361
86.6%
Uppercase Letter56
 
13.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n52
14.4%
i47
13.0%
e43
11.9%
a37
10.2%
g33
9.1%
s33
9.1%
h26
7.2%
r22
6.1%
o21
5.8%
w17
 
4.7%
Other values (7)30
8.3%
Uppercase Letter
ValueCountFrequency (%)
N17
30.4%
E16
28.6%
C7
12.5%
K4
 
7.1%
J4
 
7.1%
R3
 
5.4%
T2
 
3.6%
D1
 
1.8%
P1
 
1.8%
A1
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Latin417
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n52
12.5%
i47
11.3%
e43
10.3%
a37
8.9%
g33
 
7.9%
s33
 
7.9%
h26
 
6.2%
r22
 
5.3%
o21
 
5.0%
N17
 
4.1%
Other values (17)86
20.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n52
12.5%
i47
11.3%
e43
10.3%
a37
8.9%
g33
 
7.9%
s33
 
7.9%
h26
 
6.2%
r22
 
5.3%
o21
 
5.0%
N17
 
4.1%
Other values (17)86
20.6%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size576.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size576.0 B
Running
28 
To Be Determined
15 
Ended
13 

Length

Max length16
Median length11.5
Mean length8.946428571
Min length5

Characters and Unicode

Total characters501
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running28
50.0%
To Be Determined15
26.8%
Ended13
23.2%

Length

2022-09-05T21:38:00.499010image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:00.586004image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running28
32.6%
to15
17.4%
be15
17.4%
determined15
17.4%
ended13
15.1%

Most occurring characters

ValueCountFrequency (%)
n112
22.4%
e73
14.6%
i43
 
8.6%
d41
 
8.2%
30
 
6.0%
R28
 
5.6%
u28
 
5.6%
g28
 
5.6%
T15
 
3.0%
o15
 
3.0%
Other values (6)88
17.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter385
76.8%
Uppercase Letter86
 
17.2%
Space Separator30
 
6.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n112
29.1%
e73
19.0%
i43
 
11.2%
d41
 
10.6%
u28
 
7.3%
g28
 
7.3%
o15
 
3.9%
t15
 
3.9%
r15
 
3.9%
m15
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
R28
32.6%
T15
17.4%
B15
17.4%
D15
17.4%
E13
15.1%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin471
94.0%
Common30
 
6.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n112
23.8%
e73
15.5%
i43
 
9.1%
d41
 
8.7%
R28
 
5.9%
u28
 
5.9%
g28
 
5.9%
T15
 
3.2%
o15
 
3.2%
B15
 
3.2%
Other values (5)73
15.5%
Common
ValueCountFrequency (%)
30
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII501
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n112
22.4%
e73
14.6%
i43
 
8.6%
d41
 
8.2%
30
 
6.0%
R28
 
5.6%
u28
 
5.6%
g28
 
5.6%
T15
 
3.0%
o15
 
3.0%
Other values (6)88
17.6%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct17
Distinct (%)51.5%
Missing23
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean44.84848485
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:00.658274image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.2
Q116
median25
Q345
95-th percentile120
Maximum300
Range298
Interquartile range (IQR)29

Descriptive statistics

Standard deviation56.28283553
Coefficient of variation (CV)1.254955117
Kurtosis13.06409608
Mean44.84848485
Median Absolute Deviation (MAD)10
Skewness3.257523042
Sum1480
Variance3167.757576
MonotonicityNot monotonic
2022-09-05T21:38:00.748925image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
305
 
8.9%
204
 
7.1%
453
 
5.4%
153
 
5.4%
1203
 
5.4%
603
 
5.4%
252
 
3.6%
161
 
1.8%
21
 
1.8%
901
 
1.8%
Other values (7)7
 
12.5%
(Missing)23
41.1%
ValueCountFrequency (%)
21
 
1.8%
31
 
1.8%
51
 
1.8%
81
 
1.8%
91
 
1.8%
153
5.4%
161
 
1.8%
204
7.1%
231
 
1.8%
241
 
1.8%
ValueCountFrequency (%)
3001
 
1.8%
1203
5.4%
901
 
1.8%
603
5.4%
453
5.4%
305
8.9%
252
 
3.6%
241
 
1.8%
231
 
1.8%
204
7.1%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)62.7%
Missing5
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean37.01960784
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:00.840575image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q16
median21
Q346
95-th percentile113.5
Maximum300
Range298
Interquartile range (IQR)40

Descriptive statistics

Standard deviation51.60832886
Coefficient of variation (CV)1.394080917
Kurtosis14.30643045
Mean37.01960784
Median Absolute Deviation (MAD)16
Skewness3.433034781
Sum1888
Variance2663.419608
MonotonicityNot monotonic
2022-09-05T21:38:00.941215image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
511
19.6%
304
 
7.1%
212
 
3.6%
202
 
3.6%
252
 
3.6%
452
 
3.6%
472
 
3.6%
512
 
3.6%
161
 
1.8%
181
 
1.8%
Other values (22)22
39.3%
(Missing)5
 
8.9%
ValueCountFrequency (%)
21
 
1.8%
31
 
1.8%
511
19.6%
71
 
1.8%
81
 
1.8%
91
 
1.8%
111
 
1.8%
131
 
1.8%
151
 
1.8%
161
 
1.8%
ValueCountFrequency (%)
3001
1.8%
1941
1.8%
1291
1.8%
981
1.8%
881
1.8%
741
1.8%
601
1.8%
581
1.8%
561
1.8%
512
3.6%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct38
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size576.0 B
2020-12-05
13 
2020-11-07
 
2
2020-10-24
 
2
2020-11-14
 
2
2020-11-19
 
2
Other values (33)
35 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters560
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)55.4%

Sample

1st row2019-03-25
2nd row2015-02-13
3rd row2018-01-13
4th row2020-07-11
5th row2020-10-31

Common Values

ValueCountFrequency (%)
2020-12-0513
23.2%
2020-11-072
 
3.6%
2020-10-242
 
3.6%
2020-11-142
 
3.6%
2020-11-192
 
3.6%
2016-03-172
 
3.6%
2020-10-032
 
3.6%
2020-09-051
 
1.8%
2018-09-151
 
1.8%
2019-11-211
 
1.8%
Other values (28)28
50.0%

Length

2022-09-05T21:38:01.028093image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0513
23.2%
2020-10-242
 
3.6%
2020-11-142
 
3.6%
2020-11-192
 
3.6%
2016-03-172
 
3.6%
2020-10-032
 
3.6%
2020-11-072
 
3.6%
2009-12-191
 
1.8%
2017-10-171
 
1.8%
2012-01-021
 
1.8%
Other values (28)28
50.0%

Most occurring characters

ValueCountFrequency (%)
0150
26.8%
2117
20.9%
-112
20.0%
196
17.1%
520
 
3.6%
919
 
3.4%
713
 
2.3%
312
 
2.1%
68
 
1.4%
47
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number448
80.0%
Dash Punctuation112
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0150
33.5%
2117
26.1%
196
21.4%
520
 
4.5%
919
 
4.2%
713
 
2.9%
312
 
2.7%
68
 
1.8%
47
 
1.6%
86
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
-112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common560
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0150
26.8%
2117
20.9%
-112
20.0%
196
17.1%
520
 
3.6%
919
 
3.4%
713
 
2.3%
312
 
2.1%
68
 
1.4%
47
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0150
26.8%
2117
20.9%
-112
20.0%
196
17.1%
520
 
3.6%
919
 
3.4%
713
 
2.3%
312
 
2.1%
68
 
1.4%
47
 
1.2%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)69.2%
Missing43
Missing (%)76.8%
Memory size576.0 B
2020-12-19
2021-01-04
2020-12-26
2020-12-24
2020-12-05
Other values (4)

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters130
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)46.2%

Sample

1st row2021-01-04
2nd row2021-01-04
3rd row2020-12-24
4th row2020-12-05
5th row2021-01-02

Common Values

ValueCountFrequency (%)
2020-12-193
 
5.4%
2021-01-042
 
3.6%
2020-12-262
 
3.6%
2020-12-241
 
1.8%
2020-12-051
 
1.8%
2021-01-021
 
1.8%
2021-06-261
 
1.8%
2021-01-091
 
1.8%
2021-08-211
 
1.8%
(Missing)43
76.8%

Length

2022-09-05T21:38:01.107213image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:01.203406image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-193
23.1%
2021-01-042
15.4%
2020-12-262
15.4%
2020-12-241
 
7.7%
2020-12-051
 
7.7%
2021-01-021
 
7.7%
2021-06-261
 
7.7%
2021-01-091
 
7.7%
2021-08-211
 
7.7%

Most occurring characters

ValueCountFrequency (%)
239
30.0%
031
23.8%
-26
20.0%
121
16.2%
94
 
3.1%
64
 
3.1%
43
 
2.3%
51
 
0.8%
81
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number104
80.0%
Dash Punctuation26
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
239
37.5%
031
29.8%
121
20.2%
94
 
3.8%
64
 
3.8%
43
 
2.9%
51
 
1.0%
81
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
-26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
239
30.0%
031
23.8%
-26
20.0%
121
16.2%
94
 
3.1%
64
 
3.1%
43
 
2.3%
51
 
0.8%
81
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
30.0%
031
23.8%
-26
20.0%
121
16.2%
94
 
3.1%
64
 
3.1%
43
 
2.3%
51
 
0.8%
81
 
0.8%

_embedded.show.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct42
Distinct (%)77.8%
Missing2
Missing (%)3.6%
Memory size576.0 B
https://tv.nrk.no/serie/oteren-svenn
10 
https://www.iqiyi.com/lib/m_213579814.html
 
2
https://tv.nrk.no/serie/team-ingebrigtsen
 
2
https://www.netflix.com/title/81329144
 
2
https://www.vlive.tv/video/121637
 
1
Other values (37)
37 

Length

Max length102
Median length72
Mean length44.5
Min length19

Characters and Unicode

Total characters2403
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)70.4%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html
3rd rowhttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html
4th rowhttps://v.qq.com/detail/m/mzc00200hc38s5x.html
5th rowhttps://www.bilibili.com/tgcf

Common Values

ValueCountFrequency (%)
https://tv.nrk.no/serie/oteren-svenn10
 
17.9%
https://www.iqiyi.com/lib/m_213579814.html2
 
3.6%
https://tv.nrk.no/serie/team-ingebrigtsen2
 
3.6%
https://www.netflix.com/title/813291442
 
3.6%
https://www.vlive.tv/video/1216371
 
1.8%
https://www.discoveryplus.com/show/tregayes-way-in-the-kitchen1
 
1.8%
https://m.youtube.com/playlist?list=PLzpGYTdIrMWnRdP7POYwV4Nt-WncCRKwB1
 
1.8%
https://www.youtube.com/playlist?list=PLvahqwMqN4M2o2ZzY6Y8a626Lf286LdVl1
 
1.8%
https://shahid.mbc.net/en/series/Arous%20Beirut-season-1/season-376514-3765151
 
1.8%
https://wetv.vip/en/play/fscxgyc44dvhojy-After%20Dark/j0034ios98n-Official%20Trailer%3A%20After%20Dark1
 
1.8%
Other values (32)32
57.1%
(Missing)2
 
3.6%

Length

2022-09-05T21:38:01.305862image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://tv.nrk.no/serie/oteren-svenn10
 
18.5%
https://www.netflix.com/title/813291442
 
3.7%
https://www.iqiyi.com/lib/m_213579814.html2
 
3.7%
https://tv.nrk.no/serie/team-ingebrigtsen2
 
3.7%
https://salemsocial.kz/projects/zombeti1
 
1.9%
https://tv.kakao.com/channel/3658620/cliplink/415324903?metaobjecttype=channel1
 
1.9%
https://v.qq.com/detail/m/m441e3rjq9kwpsc.html1
 
1.9%
https://v.qq.com/detail/m/mzc00200hc38s5x.html1
 
1.9%
https://www.bilibili.com/tgcf1
 
1.9%
https://tv.nrk.no/serie/klassen1
 
1.9%
Other values (32)32
59.3%

Most occurring characters

ValueCountFrequency (%)
t219
 
9.1%
/213
 
8.9%
e160
 
6.7%
s146
 
6.1%
o113
 
4.7%
.111
 
4.6%
n106
 
4.4%
w95
 
4.0%
i94
 
3.9%
r92
 
3.8%
Other values (60)1054
43.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1718
71.5%
Other Punctuation393
 
16.4%
Decimal Number147
 
6.1%
Uppercase Letter89
 
3.7%
Dash Punctuation40
 
1.7%
Math Symbol9
 
0.4%
Connector Punctuation7
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t219
12.7%
e160
 
9.3%
s146
 
8.5%
o113
 
6.6%
n106
 
6.2%
w95
 
5.5%
i94
 
5.5%
r92
 
5.4%
h90
 
5.2%
p86
 
5.0%
Other values (16)517
30.1%
Uppercase Letter
ValueCountFrequency (%)
P11
 
12.4%
L6
 
6.7%
W6
 
6.7%
C5
 
5.6%
A5
 
5.6%
M5
 
5.6%
T5
 
5.6%
Y5
 
5.6%
B4
 
4.5%
V4
 
4.5%
Other values (15)33
37.1%
Decimal Number
ValueCountFrequency (%)
120
13.6%
020
13.6%
420
13.6%
219
12.9%
316
10.9%
814
9.5%
610
6.8%
510
6.8%
99
6.1%
79
6.1%
Other Punctuation
ValueCountFrequency (%)
/213
54.2%
.111
28.2%
:54
 
13.7%
?6
 
1.5%
%6
 
1.5%
&3
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
-40
100.0%
Math Symbol
ValueCountFrequency (%)
=9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1807
75.2%
Common596
 
24.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t219
 
12.1%
e160
 
8.9%
s146
 
8.1%
o113
 
6.3%
n106
 
5.9%
w95
 
5.3%
i94
 
5.2%
r92
 
5.1%
h90
 
5.0%
p86
 
4.8%
Other values (41)606
33.5%
Common
ValueCountFrequency (%)
/213
35.7%
.111
18.6%
:54
 
9.1%
-40
 
6.7%
120
 
3.4%
020
 
3.4%
420
 
3.4%
219
 
3.2%
316
 
2.7%
814
 
2.3%
Other values (9)69
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2403
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t219
 
9.1%
/213
 
8.9%
e160
 
6.7%
s146
 
6.1%
o113
 
4.7%
.111
 
4.6%
n106
 
4.4%
w95
 
4.0%
i94
 
3.9%
r92
 
3.8%
Other values (60)1054
43.9%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size576.0 B
40 
06:00
 
4
10:00
 
2
18:00
 
2
11:00
 
1
Other values (7)

Length

Max length5
Median length0
Mean length1.428571429
Min length0

Characters and Unicode

Total characters80
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)14.3%

Sample

1st row
2nd row
3rd row10:00
4th row10:00
5th row11:00

Common Values

ValueCountFrequency (%)
40
71.4%
06:004
 
7.1%
10:002
 
3.6%
18:002
 
3.6%
11:001
 
1.8%
17:001
 
1.8%
00:001
 
1.8%
00:151
 
1.8%
19:501
 
1.8%
16:001
 
1.8%
Other values (2)2
 
3.6%

Length

2022-09-05T21:38:01.399039image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06:004
25.0%
10:002
12.5%
18:002
12.5%
11:001
 
6.2%
17:001
 
6.2%
00:001
 
6.2%
00:151
 
6.2%
19:501
 
6.2%
16:001
 
6.2%
19:301
 
6.2%

Most occurring characters

ValueCountFrequency (%)
038
47.5%
:16
20.0%
111
 
13.8%
65
 
6.2%
82
 
2.5%
52
 
2.5%
92
 
2.5%
22
 
2.5%
71
 
1.2%
31
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number64
80.0%
Other Punctuation16
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
038
59.4%
111
 
17.2%
65
 
7.8%
82
 
3.1%
52
 
3.1%
92
 
3.1%
22
 
3.1%
71
 
1.6%
31
 
1.6%
Other Punctuation
ValueCountFrequency (%)
:16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common80
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
038
47.5%
:16
20.0%
111
 
13.8%
65
 
6.2%
82
 
2.5%
52
 
2.5%
92
 
2.5%
22
 
2.5%
71
 
1.2%
31
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
038
47.5%
:16
20.0%
111
 
13.8%
65
 
6.2%
82
 
2.5%
52
 
2.5%
92
 
2.5%
22
 
2.5%
71
 
1.2%
31
 
1.2%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size576.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3
Distinct (%)60.0%
Missing51
Missing (%)91.1%
Memory size576.0 B
7.7
7.3
5.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters15
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st row7.7
2nd row7.3
3rd row7.7
4th row5.0
5th row7.7

Common Values

ValueCountFrequency (%)
7.73
 
5.4%
7.31
 
1.8%
5.01
 
1.8%
(Missing)51
91.1%

Length

2022-09-05T21:38:01.478461image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:01.559994image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.73
60.0%
7.31
 
20.0%
5.01
 
20.0%

Most occurring characters

ValueCountFrequency (%)
77
46.7%
.5
33.3%
31
 
6.7%
51
 
6.7%
01
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number10
66.7%
Other Punctuation5
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
77
70.0%
31
 
10.0%
51
 
10.0%
01
 
10.0%
Other Punctuation
ValueCountFrequency (%)
.5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
77
46.7%
.5
33.3%
31
 
6.7%
51
 
6.7%
01
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
46.7%
.5
33.3%
31
 
6.7%
51
 
6.7%
01
 
6.7%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct34
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.14285714
Minimum1
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:01.642158image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q17
median27
Q345
95-th percentile82.75
Maximum95
Range94
Interquartile range (IQR)38

Descriptive statistics

Standard deviation25.70067461
Coefficient of variation (CV)0.7995765434
Kurtosis-0.07624743984
Mean32.14285714
Median Absolute Deviation (MAD)19
Skewness0.8428463502
Sum1800
Variance660.5246753
MonotonicityNot monotonic
2022-09-05T21:38:01.745768image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
711
19.6%
223
 
5.4%
292
 
3.6%
12
 
3.6%
452
 
3.6%
632
 
3.6%
342
 
3.6%
82
 
3.6%
192
 
3.6%
422
 
3.6%
Other values (24)26
46.4%
ValueCountFrequency (%)
12
 
3.6%
21
 
1.8%
41
 
1.8%
711
19.6%
82
 
3.6%
91
 
1.8%
181
 
1.8%
192
 
3.6%
201
 
1.8%
223
 
5.4%
ValueCountFrequency (%)
951
1.8%
921
1.8%
911
1.8%
801
1.8%
791
1.8%
741
1.8%
651
1.8%
632
3.6%
621
1.8%
521
1.8%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct28
Distinct (%)50.9%
Missing1
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean166.8
Minimum1
Maximum533
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:01.837819image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.5
Q125.5
median173
Q3238
95-th percentile370.6
Maximum533
Range532
Interquartile range (IQR)212.5

Descriptive statistics

Standard deviation132.5227304
Coefficient of variation (CV)0.7945007818
Kurtosis-0.4408069455
Mean166.8
Median Absolute Deviation (MAD)119
Skewness0.4840015422
Sum9174
Variance17562.27407
MonotonicityNot monotonic
2022-09-05T21:38:01.943834image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
23816
28.6%
219
16.1%
1042
 
3.6%
12
 
3.6%
1182
 
3.6%
202
 
3.6%
1221
 
1.8%
3421
 
1.8%
3671
 
1.8%
5331
 
1.8%
Other values (18)18
32.1%
ValueCountFrequency (%)
12
 
3.6%
151
 
1.8%
202
 
3.6%
219
16.1%
301
 
1.8%
321
 
1.8%
451
 
1.8%
511
 
1.8%
541
 
1.8%
561
 
1.8%
ValueCountFrequency (%)
5331
1.8%
4521
1.8%
3791
1.8%
3671
1.8%
3471
1.8%
3421
1.8%
3271
1.8%
3191
1.8%
2941
1.8%
2651
1.8%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct28
Distinct (%)50.9%
Missing1
Missing (%)1.8%
Memory size576.0 B
NRK TV
16 
YouTube
Tencent QQ
 
2
Netflix
 
2
Youku
 
2
Other values (23)
24 

Length

Max length14
Median length13
Mean length7.327272727
Min length4

Characters and Unicode

Total characters403
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)40.0%

Sample

1st rowV LIVE
2nd rowSeasonvar
3rd rowTencent QQ
4th rowTencent QQ
5th rowBilibili

Common Values

ValueCountFrequency (%)
NRK TV16
28.6%
YouTube9
16.1%
Tencent QQ2
 
3.6%
Netflix2
 
3.6%
Youku2
 
3.6%
Crunchyroll2
 
3.6%
V LIVE1
 
1.8%
Paravi1
 
1.8%
WeTV1
 
1.8%
TELASA1
 
1.8%
Other values (18)18
32.1%

Length

2022-09-05T21:38:02.044479image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tv19
22.4%
nrk16
18.8%
youtube9
 
10.6%
tencent2
 
2.4%
qq2
 
2.4%
netflix2
 
2.4%
youku2
 
2.4%
crunchyroll2
 
2.4%
naver1
 
1.2%
seasonvar1
 
1.2%
Other values (29)29
34.1%

Most occurring characters

ValueCountFrequency (%)
T36
 
8.9%
30
 
7.4%
e27
 
6.7%
u26
 
6.5%
V25
 
6.2%
N23
 
5.7%
o22
 
5.5%
K17
 
4.2%
R17
 
4.2%
a12
 
3.0%
Other values (37)168
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter195
48.4%
Uppercase Letter174
43.2%
Space Separator30
 
7.4%
Math Symbol2
 
0.5%
Other Punctuation1
 
0.2%
Decimal Number1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e27
13.8%
u26
13.3%
o22
11.3%
a12
 
6.2%
b12
 
6.2%
i12
 
6.2%
l11
 
5.6%
r11
 
5.6%
t11
 
5.6%
n8
 
4.1%
Other values (12)43
22.1%
Uppercase Letter
ValueCountFrequency (%)
T36
20.7%
V25
14.4%
N23
13.2%
K17
9.8%
R17
9.8%
Y11
 
6.3%
P6
 
3.4%
E5
 
2.9%
W5
 
2.9%
S4
 
2.3%
Other values (11)25
14.4%
Space Separator
ValueCountFrequency (%)
30
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%
Decimal Number
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin369
91.6%
Common34
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
T36
 
9.8%
e27
 
7.3%
u26
 
7.0%
V25
 
6.8%
N23
 
6.2%
o22
 
6.0%
K17
 
4.6%
R17
 
4.6%
a12
 
3.3%
b12
 
3.3%
Other values (33)152
41.2%
Common
ValueCountFrequency (%)
30
88.2%
+2
 
5.9%
.1
 
2.9%
21
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII403
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T36
 
8.9%
30
 
7.4%
e27
 
6.7%
u26
 
6.5%
V25
 
6.2%
N23
 
5.7%
o22
 
5.5%
K17
 
4.2%
R17
 
4.2%
a12
 
3.0%
Other values (37)168
41.7%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)21.6%
Missing19
Missing (%)33.9%
Memory size576.0 B
Norway
17 
China
United States
Korea, Republic of
Japan
Other values (3)

Length

Max length18
Median length14
Mean length8.675675676
Min length5

Characters and Unicode

Total characters321
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)8.1%

Sample

1st rowKorea, Republic of
2nd rowRussian Federation
3rd rowChina
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
Norway17
30.4%
China5
 
8.9%
United States5
 
8.9%
Korea, Republic of4
 
7.1%
Japan3
 
5.4%
Russian Federation1
 
1.8%
United Kingdom1
 
1.8%
Kazakhstan1
 
1.8%
(Missing)19
33.9%

Length

2022-09-05T21:38:02.141316image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:02.246865image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
norway17
32.7%
united6
 
11.5%
china5
 
9.6%
states5
 
9.6%
korea4
 
7.7%
republic4
 
7.7%
of4
 
7.7%
japan3
 
5.8%
russian1
 
1.9%
federation1
 
1.9%
Other values (2)2
 
3.8%

Most occurring characters

ValueCountFrequency (%)
a42
13.1%
o27
 
8.4%
r22
 
6.9%
e21
 
6.5%
i18
 
5.6%
n18
 
5.6%
t18
 
5.6%
N17
 
5.3%
w17
 
5.3%
y17
 
5.3%
Other values (22)104
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter254
79.1%
Uppercase Letter48
 
15.0%
Space Separator15
 
4.7%
Other Punctuation4
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a42
16.5%
o27
10.6%
r22
8.7%
e21
8.3%
i18
 
7.1%
n18
 
7.1%
t18
 
7.1%
w17
 
6.7%
y17
 
6.7%
d8
 
3.1%
Other values (12)46
18.1%
Uppercase Letter
ValueCountFrequency (%)
N17
35.4%
U6
 
12.5%
K6
 
12.5%
S5
 
10.4%
C5
 
10.4%
R5
 
10.4%
J3
 
6.2%
F1
 
2.1%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
,4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin302
94.1%
Common19
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a42
13.9%
o27
 
8.9%
r22
 
7.3%
e21
 
7.0%
i18
 
6.0%
n18
 
6.0%
t18
 
6.0%
N17
 
5.6%
w17
 
5.6%
y17
 
5.6%
Other values (20)85
28.1%
Common
ValueCountFrequency (%)
15
78.9%
,4
 
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a42
13.1%
o27
 
8.4%
r22
 
6.9%
e21
 
6.5%
i18
 
5.6%
n18
 
5.6%
t18
 
5.6%
N17
 
5.3%
w17
 
5.3%
y17
 
5.3%
Other values (22)104
32.4%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)21.6%
Missing19
Missing (%)33.9%
Memory size576.0 B
NO
17 
CN
US
KR
JP
Other values (3)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters74
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)8.1%

Sample

1st rowKR
2nd rowRU
3rd rowCN
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
NO17
30.4%
CN5
 
8.9%
US5
 
8.9%
KR4
 
7.1%
JP3
 
5.4%
RU1
 
1.8%
GB1
 
1.8%
KZ1
 
1.8%
(Missing)19
33.9%

Length

2022-09-05T21:38:02.339647image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:02.440328image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
no17
45.9%
cn5
 
13.5%
us5
 
13.5%
kr4
 
10.8%
jp3
 
8.1%
ru1
 
2.7%
gb1
 
2.7%
kz1
 
2.7%

Most occurring characters

ValueCountFrequency (%)
N22
29.7%
O17
23.0%
U6
 
8.1%
C5
 
6.8%
S5
 
6.8%
K5
 
6.8%
R5
 
6.8%
J3
 
4.1%
P3
 
4.1%
G1
 
1.4%
Other values (2)2
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter74
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N22
29.7%
O17
23.0%
U6
 
8.1%
C5
 
6.8%
S5
 
6.8%
K5
 
6.8%
R5
 
6.8%
J3
 
4.1%
P3
 
4.1%
G1
 
1.4%
Other values (2)2
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Latin74
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N22
29.7%
O17
23.0%
U6
 
8.1%
C5
 
6.8%
S5
 
6.8%
K5
 
6.8%
R5
 
6.8%
J3
 
4.1%
P3
 
4.1%
G1
 
1.4%
Other values (2)2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII74
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N22
29.7%
O17
23.0%
U6
 
8.1%
C5
 
6.8%
S5
 
6.8%
K5
 
6.8%
R5
 
6.8%
J3
 
4.1%
P3
 
4.1%
G1
 
1.4%
Other values (2)2
 
2.7%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)21.6%
Missing19
Missing (%)33.9%
Memory size576.0 B
Europe/Oslo
17 
Asia/Shanghai
America/New_York
Asia/Seoul
Asia/Tokyo
Other values (3)

Length

Max length16
Median length14
Mean length11.97297297
Min length10

Characters and Unicode

Total characters443
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)8.1%

Sample

1st rowAsia/Seoul
2nd rowAsia/Kamchatka
3rd rowAsia/Shanghai
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Europe/Oslo17
30.4%
Asia/Shanghai5
 
8.9%
America/New_York5
 
8.9%
Asia/Seoul4
 
7.1%
Asia/Tokyo3
 
5.4%
Asia/Kamchatka1
 
1.8%
Europe/London1
 
1.8%
Asia/Qyzylorda1
 
1.8%
(Missing)19
33.9%

Length

2022-09-05T21:38:04.223735image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:04.327110image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/oslo17
45.9%
asia/shanghai5
 
13.5%
america/new_york5
 
13.5%
asia/seoul4
 
10.8%
asia/tokyo3
 
8.1%
asia/kamchatka1
 
2.7%
europe/london1
 
2.7%
asia/qyzylorda1
 
2.7%

Most occurring characters

ValueCountFrequency (%)
o53
 
12.0%
/37
 
8.4%
a33
 
7.4%
e32
 
7.2%
s31
 
7.0%
r29
 
6.5%
i24
 
5.4%
u22
 
5.0%
l22
 
5.0%
A19
 
4.3%
Other values (22)141
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter322
72.7%
Uppercase Letter79
 
17.8%
Other Punctuation37
 
8.4%
Connector Punctuation5
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o53
16.5%
a33
10.2%
e32
9.9%
s31
9.6%
r29
9.0%
i24
7.5%
u22
6.8%
l22
6.8%
p18
 
5.6%
h11
 
3.4%
Other values (10)47
14.6%
Uppercase Letter
ValueCountFrequency (%)
A19
24.1%
E18
22.8%
O17
21.5%
S9
11.4%
Y5
 
6.3%
N5
 
6.3%
T3
 
3.8%
K1
 
1.3%
L1
 
1.3%
Q1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin401
90.5%
Common42
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o53
13.2%
a33
 
8.2%
e32
 
8.0%
s31
 
7.7%
r29
 
7.2%
i24
 
6.0%
u22
 
5.5%
l22
 
5.5%
A19
 
4.7%
E18
 
4.5%
Other values (20)118
29.4%
Common
ValueCountFrequency (%)
/37
88.1%
_5
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o53
 
12.0%
/37
 
8.4%
a33
 
7.4%
e32
 
7.2%
s31
 
7.0%
r29
 
6.5%
i24
 
5.4%
u22
 
5.0%
l22
 
5.0%
A19
 
4.3%
Other values (22)141
31.8%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct11
Distinct (%)52.4%
Missing35
Missing (%)62.5%
Memory size576.0 B
https://www.youtube.com
https://v.qq.com/
https://www.netflix.com/
https://www.vlive.tv/home
https://tv.kakao.com/top
Other values (6)

Length

Max length34
Median length30
Mean length23.23809524
Min length17

Characters and Unicode

Total characters488
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)38.1%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://tv.kakao.com/top
5th rowhttps://www.melon.com/tv/index.htm

Common Values

ValueCountFrequency (%)
https://www.youtube.com9
 
16.1%
https://v.qq.com/2
 
3.6%
https://www.netflix.com/2
 
3.6%
https://www.vlive.tv/home1
 
1.8%
https://tv.kakao.com/top1
 
1.8%
https://www.melon.com/tv/index.htm1
 
1.8%
https://tv.naver.com/1
 
1.8%
https://www.linetv.tw/1
 
1.8%
https://www.discoveryplus.com/1
 
1.8%
https://wetv.vip/1
 
1.8%
(Missing)35
62.5%

Length

2022-09-05T21:38:04.425535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com9
42.9%
https://v.qq.com2
 
9.5%
https://www.netflix.com2
 
9.5%
https://www.vlive.tv/home1
 
4.8%
https://tv.kakao.com/top1
 
4.8%
https://www.melon.com/tv/index.htm1
 
4.8%
https://tv.naver.com1
 
4.8%
https://www.linetv.tw1
 
4.8%
https://www.discoveryplus.com1
 
4.8%
https://wetv.vip1
 
4.8%

Most occurring characters

ValueCountFrequency (%)
t63
12.9%
/55
11.3%
w50
 
10.2%
.42
 
8.6%
o33
 
6.8%
p25
 
5.1%
h23
 
4.7%
s23
 
4.7%
m21
 
4.3%
c21
 
4.3%
Other values (16)132
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter370
75.8%
Other Punctuation118
 
24.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t63
17.0%
w50
13.5%
o33
8.9%
p25
 
6.8%
h23
 
6.2%
s23
 
6.2%
m21
 
5.7%
c21
 
5.7%
e20
 
5.4%
u19
 
5.1%
Other values (13)72
19.5%
Other Punctuation
ValueCountFrequency (%)
/55
46.6%
.42
35.6%
:21
 
17.8%

Most occurring scripts

ValueCountFrequency (%)
Latin370
75.8%
Common118
 
24.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t63
17.0%
w50
13.5%
o33
8.9%
p25
 
6.8%
h23
 
6.2%
s23
 
6.2%
m21
 
5.7%
c21
 
5.7%
e20
 
5.4%
u19
 
5.1%
Other values (13)72
19.5%
Common
ValueCountFrequency (%)
/55
46.6%
.42
35.6%
:21
 
17.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t63
12.9%
/55
11.3%
w50
 
10.2%
.42
 
8.6%
o33
 
6.8%
p25
 
5.1%
h23
 
4.7%
s23
 
4.7%
m21
 
4.3%
c21
 
4.3%
Other values (16)132
27.0%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing54
Missing (%)96.4%
Memory size576.0 B
38292.0
15090.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row38292.0
2nd row15090.0

Common Values

ValueCountFrequency (%)
38292.01
 
1.8%
15090.01
 
1.8%
(Missing)54
96.4%

Length

2022-09-05T21:38:04.518193image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:04.605338image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
38292.01
50.0%
15090.01
50.0%

Most occurring characters

ValueCountFrequency (%)
04
28.6%
22
14.3%
92
14.3%
.2
14.3%
31
 
7.1%
81
 
7.1%
11
 
7.1%
51
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12
85.7%
Other Punctuation2
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
04
33.3%
22
16.7%
92
16.7%
31
 
8.3%
81
 
8.3%
11
 
8.3%
51
 
8.3%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
04
28.6%
22
14.3%
92
14.3%
.2
14.3%
31
 
7.1%
81
 
7.1%
11
 
7.1%
51
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
04
28.6%
22
14.3%
92
14.3%
.2
14.3%
31
 
7.1%
81
 
7.1%
11
 
7.1%
51
 
7.1%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct30
Distinct (%)90.9%
Missing23
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean352367.697
Minimum253990
Maximum397581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:04.685107image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum253990
5-th percentile264715.4
Q1331095
median361541
Q3387152
95-th percentile393539.8
Maximum397581
Range143591
Interquartile range (IQR)56057

Descriptive statistics

Standard deviation40393.31194
Coefficient of variation (CV)0.1146339812
Kurtosis0.2446602159
Mean352367.697
Median Absolute Deviation (MAD)27131
Skewness-0.9610248961
Sum11628134
Variance1631619650
MonotonicityNot monotonic
2022-09-05T21:38:04.787792image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3871522
 
3.6%
3310952
 
3.6%
3434742
 
3.6%
3894171
 
1.8%
3226731
 
1.8%
3697981
 
1.8%
3908731
 
1.8%
3871301
 
1.8%
3166901
 
1.8%
2639991
 
1.8%
Other values (20)20
35.7%
(Missing)23
41.1%
ValueCountFrequency (%)
2539901
1.8%
2639991
1.8%
2651931
1.8%
2999651
1.8%
3166901
1.8%
3226731
1.8%
3227211
1.8%
3229061
1.8%
3310952
3.6%
3386871
1.8%
ValueCountFrequency (%)
3975811
1.8%
3948761
1.8%
3926491
1.8%
3915281
1.8%
3908731
1.8%
3894171
1.8%
3886721
1.8%
3871522
3.6%
3871301
1.8%
3865771
1.8%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct19
Distinct (%)61.3%
Missing25
Missing (%)44.6%
Memory size576.0 B
tt14128050
10 
tt8871128
tt5677376
tt13175760
tt12457946
 
1
Other values (14)
14 

Length

Max length10
Median length10
Mean length9.709677419
Min length9

Characters and Unicode

Total characters301
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)48.4%

Sample

1st rowtt13375866
2nd rowtt8871128
3rd rowtt8871128
4th rowtt10960302
5th rowtt5677376

Common Values

ValueCountFrequency (%)
tt1412805010
 
17.9%
tt88711282
 
3.6%
tt56773762
 
3.6%
tt131757602
 
3.6%
tt124579461
 
1.8%
tt88514441
 
1.8%
tt135107341
 
1.8%
tt133995381
 
1.8%
tt125849001
 
1.8%
tt30662421
 
1.8%
Other values (9)9
 
16.1%
(Missing)25
44.6%

Length

2022-09-05T21:38:04.879070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt1412805010
32.3%
tt56773762
 
6.5%
tt131757602
 
6.5%
tt88711282
 
6.5%
tt140284101
 
3.2%
tt109603021
 
3.2%
tt114923201
 
3.2%
tt20430311
 
3.2%
tt63440821
 
3.2%
tt133758661
 
3.2%
Other values (9)9
29.0%

Most occurring characters

ValueCountFrequency (%)
t62
20.6%
143
14.3%
037
12.3%
426
8.6%
826
8.6%
225
8.3%
524
 
8.0%
618
 
6.0%
318
 
6.0%
715
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number239
79.4%
Lowercase Letter62
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
143
18.0%
037
15.5%
426
10.9%
826
10.9%
225
10.5%
524
10.0%
618
7.5%
318
7.5%
715
 
6.3%
97
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
t62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common239
79.4%
Latin62
 
20.6%

Most frequent character per script

Common
ValueCountFrequency (%)
143
18.0%
037
15.5%
426
10.9%
826
10.9%
225
10.5%
524
10.0%
618
7.5%
318
7.5%
715
 
6.3%
97
 
2.9%
Latin
ValueCountFrequency (%)
t62
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII301
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t62
20.6%
143
14.3%
037
12.3%
426
8.6%
826
8.6%
225
8.3%
524
 
8.0%
618
 
6.0%
318
 
6.0%
715
 
5.0%

_embedded.show.image.medium
Categorical

HIGH CORRELATION
MISSING

Distinct42
Distinct (%)77.8%
Missing2
Missing (%)3.6%
Memory size576.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/351/879432.jpg
10 
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/379/948814.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/403/1008990.jpg
 
1
Other values (37)
37 

Length

Max length72
Median length71
Mean length71.07407407
Min length69

Characters and Unicode

Total characters3838
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)70.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/294/735323.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/150/375304.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/414/1036502.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/351/879432.jpg10
 
17.9%
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/379/948814.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/medium_portrait/403/1008990.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/298/745789.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/332/831639.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/361/903289.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/398/996515.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/406/1015108.jpg1
 
1.8%
Other values (32)32
57.1%
(Missing)2
 
3.6%

Length

2022-09-05T21:38:04.962905image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/351/879432.jpg10
 
18.5%
https://static.tvmaze.com/uploads/images/medium_portrait/379/948814.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713500.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/275/688802.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/294/735323.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/150/375304.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/medium_portrait/414/1036502.jpg1
 
1.9%
Other values (32)32
59.3%

Most occurring characters

ValueCountFrequency (%)
t378
 
9.8%
/378
 
9.8%
a270
 
7.0%
m270
 
7.0%
p216
 
5.6%
s216
 
5.6%
i216
 
5.6%
.162
 
4.2%
e162
 
4.2%
o162
 
4.2%
Other values (22)1408
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2700
70.3%
Other Punctuation594
 
15.5%
Decimal Number490
 
12.8%
Connector Punctuation54
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t378
14.0%
a270
10.0%
m270
10.0%
p216
 
8.0%
s216
 
8.0%
i216
 
8.0%
e162
 
6.0%
o162
 
6.0%
g108
 
4.0%
c108
 
4.0%
Other values (8)594
22.0%
Decimal Number
ValueCountFrequency (%)
377
15.7%
957
11.6%
754
11.0%
253
10.8%
150
10.2%
448
9.8%
842
8.6%
540
8.2%
038
7.8%
631
6.3%
Other Punctuation
ValueCountFrequency (%)
/378
63.6%
.162
27.3%
:54
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2700
70.3%
Common1138
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t378
14.0%
a270
10.0%
m270
10.0%
p216
 
8.0%
s216
 
8.0%
i216
 
8.0%
e162
 
6.0%
o162
 
6.0%
g108
 
4.0%
c108
 
4.0%
Other values (8)594
22.0%
Common
ValueCountFrequency (%)
/378
33.2%
.162
14.2%
377
 
6.8%
957
 
5.0%
754
 
4.7%
_54
 
4.7%
:54
 
4.7%
253
 
4.7%
150
 
4.4%
448
 
4.2%
Other values (4)151
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII3838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t378
 
9.8%
/378
 
9.8%
a270
 
7.0%
m270
 
7.0%
p216
 
5.6%
s216
 
5.6%
i216
 
5.6%
.162
 
4.2%
e162
 
4.2%
o162
 
4.2%
Other values (22)1408
36.7%

_embedded.show.image.original
Categorical

HIGH CORRELATION
MISSING

Distinct42
Distinct (%)77.8%
Missing2
Missing (%)3.6%
Memory size576.0 B
https://static.tvmaze.com/uploads/images/original_untouched/351/879432.jpg
10 
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/379/948814.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/403/1008990.jpg
 
1
Other values (37)
37 

Length

Max length75
Median length74
Mean length74.07407407
Min length72

Characters and Unicode

Total characters4000
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)70.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/735323.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/150/375304.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/414/1036502.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/351/879432.jpg10
 
17.9%
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/379/948814.jpg2
 
3.6%
https://static.tvmaze.com/uploads/images/original_untouched/403/1008990.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/298/745789.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/332/831639.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/361/903289.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/398/996515.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/406/1015108.jpg1
 
1.8%
Other values (32)32
57.1%
(Missing)2
 
3.6%

Length

2022-09-05T21:38:05.052695image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/351/879432.jpg10
 
18.5%
https://static.tvmaze.com/uploads/images/original_untouched/379/948814.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg2
 
3.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/713500.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/275/688802.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/294/735323.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/150/375304.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg1
 
1.9%
https://static.tvmaze.com/uploads/images/original_untouched/414/1036502.jpg1
 
1.9%
Other values (32)32
59.3%

Most occurring characters

ValueCountFrequency (%)
/378
 
9.4%
t324
 
8.1%
a270
 
6.8%
s216
 
5.4%
i216
 
5.4%
o216
 
5.4%
p162
 
4.0%
c162
 
4.0%
.162
 
4.0%
g162
 
4.0%
Other values (23)1732
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2862
71.5%
Other Punctuation594
 
14.8%
Decimal Number490
 
12.2%
Connector Punctuation54
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t324
 
11.3%
a270
 
9.4%
s216
 
7.5%
i216
 
7.5%
o216
 
7.5%
p162
 
5.7%
c162
 
5.7%
g162
 
5.7%
m162
 
5.7%
e162
 
5.7%
Other values (9)810
28.3%
Decimal Number
ValueCountFrequency (%)
377
15.7%
957
11.6%
754
11.0%
253
10.8%
150
10.2%
448
9.8%
842
8.6%
540
8.2%
038
7.8%
631
6.3%
Other Punctuation
ValueCountFrequency (%)
/378
63.6%
.162
27.3%
:54
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2862
71.5%
Common1138
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t324
 
11.3%
a270
 
9.4%
s216
 
7.5%
i216
 
7.5%
o216
 
7.5%
p162
 
5.7%
c162
 
5.7%
g162
 
5.7%
m162
 
5.7%
e162
 
5.7%
Other values (9)810
28.3%
Common
ValueCountFrequency (%)
/378
33.2%
.162
14.2%
377
 
6.8%
957
 
5.0%
:54
 
4.7%
_54
 
4.7%
754
 
4.7%
253
 
4.7%
150
 
4.4%
448
 
4.2%
Other values (4)151
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/378
 
9.4%
t324
 
8.1%
a270
 
6.8%
s216
 
5.4%
i216
 
5.4%
o216
 
5.4%
p162
 
4.0%
c162
 
4.0%
.162
 
4.0%
g162
 
4.0%
Other values (23)1732
43.3%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING

Distinct42
Distinct (%)77.8%
Missing2
Missing (%)3.6%
Memory size576.0 B
<p>A small otter cub moves under the terrace of the Veie-Rosvoll family. It is named Svenn and quickly becomes a good friend.</p>
10 
<p><b>Detention</b> starts at Greenwood High School in the 1990s. Yunxiang Liu, a transfer student, steps into the forbidden area on the campus by accident, where she encounters the ghost of Ruixin Fang. Fang later unveils the hidden history and trauma over the past 30 years, and how a group of young students and teachers were persecuted as they fought for freedom in the era of censorship. Their stories keep coming back to the school like haunting nightmares, waiting to be told and revealed.  </p>
 
2
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>
 
2
<p>A documentary series about the running family Ingebrigtsen.</p>
 
2
<p>Comedian Yamasato Ryota enters a cafe to prepare a story. Trivial incidents unfold there with the staff, TV people, the manager, and a handsome office worker. Little things bother them, and Yamasato's annoyance reaches its limit. He pulls up his glasses, opens his notebook, and begins to write a story featuring a real-life actress in his notebook. For Yamasato, escaping reality is a "dream time" where he can forget the bad things. This is the start of Ryota Yamazato's fantasy story with the latest actresses and idols as the heroines! <br /> </p>
 
1
Other values (37)
37 

Length

Max length1620
Median length445.5
Mean length355.5555556
Min length53

Characters and Unicode

Total characters19200
Distinct characters80
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)70.4%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>
3rd row<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>
4th row<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>
5th row<p>"Have you heard? The rubbish Heaven Official is having an affair with the ghost realm's number one bigshot!"</p><p>Eight hundred years ago, Xie Lian was the Crown Prince of the Xian Le kingdom; one who was beloved by his citizens and the darling of the world. Unsurprisingly, he ascended to the Heavens at a very young age. Now, eight hundred years later, Xie Lian ascends to the Heavens for the third time as the laughing stock of all three realms. On his first task as a god, he meets a mysterious demon who rules the ghosts and terrifies the Heavens... yet unbeknownst to Xie Lian, this demon king has been paying attention to him for a very, very long time.</p>

Common Values

ValueCountFrequency (%)
<p>A small otter cub moves under the terrace of the Veie-Rosvoll family. It is named Svenn and quickly becomes a good friend.</p>10
 
17.9%
<p><b>Detention</b> starts at Greenwood High School in the 1990s. Yunxiang Liu, a transfer student, steps into the forbidden area on the campus by accident, where she encounters the ghost of Ruixin Fang. Fang later unveils the hidden history and trauma over the past 30 years, and how a group of young students and teachers were persecuted as they fought for freedom in the era of censorship. Their stories keep coming back to the school like haunting nightmares, waiting to be told and revealed.  </p>2
 
3.6%
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>2
 
3.6%
<p>A documentary series about the running family Ingebrigtsen.</p>2
 
3.6%
<p>Comedian Yamasato Ryota enters a cafe to prepare a story. Trivial incidents unfold there with the staff, TV people, the manager, and a handsome office worker. Little things bother them, and Yamasato's annoyance reaches its limit. He pulls up his glasses, opens his notebook, and begins to write a story featuring a real-life actress in his notebook. For Yamasato, escaping reality is a "dream time" where he can forget the bad things. This is the start of Ryota Yamazato's fantasy story with the latest actresses and idols as the heroines! <br /> </p>1
 
1.8%
<p>Atlanta-based chef and caterer Tregaye Fraser packs flavor and personality into every recipe, sharing her food with the ones she loves -- family, friends and her two growing boys.</p>1
 
1.8%
<p>The web series revolves around the life of university students.</p>1
 
1.8%
<p><b>I Like to Watch</b> is a 2019 American web series hosted by drag queens Trixie Mattel and Katya Zamolodchikova. The series was created by Fran Tirado, produced by Netflix, and streams on the network's YouTube channel. Produced in a similar format to Mattel and Zamolodchikova's web series <i>UNHhhh</i> and <i>The Trixie &amp; Katya Show</i>, <i>I Like to Watch</i> follows its hosts as they view and react to various Netflix Original Programming.</p>1
 
1.8%
<p>FUN EDUCATIONAL videos for children! Kids will learn colors, learn shapes, learn numbers, learn letters, the alphabet, abc's and so much more with Blippi's nursery rhymes, educational songs, and educational videos! Blippi ties in things children love like Backhoes, Tractors, Planes, Trains, Animals, Boats, Unicorns, Construction Equipment, Firetrucks, Horses, and the list goes on! Incorporating cartoons and animation with real life footage!</p>1
 
1.8%
<p>Living with her aunt, kind-hearted Thourayya leads a simple life, but her world is upended when she crosses paths with the handsome and ambitious Fares.</p>1
 
1.8%
Other values (32)32
57.1%
(Missing)2
 
3.6%

Length

2022-09-05T21:38:05.166914image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the221
 
7.0%
and127
 
4.0%
of92
 
2.9%
a85
 
2.7%
to67
 
2.1%
in52
 
1.6%
is43
 
1.4%
as34
 
1.1%
for28
 
0.9%
by25
 
0.8%
Other values (1235)2392
75.6%

Most occurring characters

ValueCountFrequency (%)
3106
16.2%
e1771
 
9.2%
t1223
 
6.4%
a1194
 
6.2%
o1079
 
5.6%
n1078
 
5.6%
i1060
 
5.5%
s986
 
5.1%
r885
 
4.6%
h734
 
3.8%
Other values (70)6084
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14421
75.1%
Space Separator3115
 
16.2%
Uppercase Letter687
 
3.6%
Other Punctuation529
 
2.8%
Math Symbol356
 
1.9%
Dash Punctuation41
 
0.2%
Decimal Number32
 
0.2%
Open Punctuation9
 
< 0.1%
Close Punctuation9
 
< 0.1%
Initial Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1771
12.3%
t1223
 
8.5%
a1194
 
8.3%
o1079
 
7.5%
n1078
 
7.5%
i1060
 
7.4%
s986
 
6.8%
r885
 
6.1%
h734
 
5.1%
d574
 
4.0%
Other values (17)3837
26.6%
Uppercase Letter
ValueCountFrequency (%)
T77
 
11.2%
S56
 
8.2%
I46
 
6.7%
A44
 
6.4%
C36
 
5.2%
L36
 
5.2%
F35
 
5.1%
W35
 
5.1%
H32
 
4.7%
B27
 
3.9%
Other values (16)263
38.3%
Other Punctuation
ValueCountFrequency (%)
,191
36.1%
.159
30.1%
/91
17.2%
'36
 
6.8%
"18
 
3.4%
!18
 
3.4%
;4
 
0.8%
:4
 
0.8%
?4
 
0.8%
3
 
0.6%
Decimal Number
ValueCountFrequency (%)
910
31.2%
07
21.9%
16
18.8%
34
 
12.5%
23
 
9.4%
41
 
3.1%
71
 
3.1%
Space Separator
ValueCountFrequency (%)
3106
99.7%
 9
 
0.3%
Math Symbol
ValueCountFrequency (%)
>178
50.0%
<178
50.0%
Dash Punctuation
ValueCountFrequency (%)
-34
82.9%
7
 
17.1%
Open Punctuation
ValueCountFrequency (%)
(9
100.0%
Close Punctuation
ValueCountFrequency (%)
)9
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin15108
78.7%
Common4092
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1771
 
11.7%
t1223
 
8.1%
a1194
 
7.9%
o1079
 
7.1%
n1078
 
7.1%
i1060
 
7.0%
s986
 
6.5%
r885
 
5.9%
h734
 
4.9%
d574
 
3.8%
Other values (43)4524
29.9%
Common
ValueCountFrequency (%)
3106
75.9%
,191
 
4.7%
>178
 
4.3%
<178
 
4.3%
.159
 
3.9%
/91
 
2.2%
'36
 
0.9%
-34
 
0.8%
"18
 
0.4%
!18
 
0.4%
Other values (17)83
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII19179
99.9%
Punctuation11
 
0.1%
None10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3106
16.2%
e1771
 
9.2%
t1223
 
6.4%
a1194
 
6.2%
o1079
 
5.6%
n1078
 
5.6%
i1060
 
5.5%
s986
 
5.1%
r885
 
4.6%
h734
 
3.8%
Other values (65)6063
31.6%
None
ValueCountFrequency (%)
 9
90.0%
æ1
 
10.0%
Punctuation
ValueCountFrequency (%)
7
63.6%
3
27.3%
1
 
9.1%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct44
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1639635438
Minimum1607104092
Maximum1662290859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size576.0 B
2022-09-05T21:38:05.277960image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1607104092
5-th percentile1609755358
Q11629906651
median1640381442
Q31651273526
95-th percentile1662239256
Maximum1662290859
Range55186767
Interquartile range (IQR)21366875.25

Descriptive statistics

Standard deviation16099193.49
Coefficient of variation (CV)0.009818764049
Kurtosis-0.7461101355
Mean1639635438
Median Absolute Deviation (MAD)10476810.5
Skewness-0.297408608
Sum9.181958453 × 1010
Variance2.591840311 × 1014
MonotonicityNot monotonic
2022-09-05T21:38:05.387406image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
162990665110
 
17.9%
16482170292
 
3.6%
16403814422
 
3.6%
16098872012
 
3.6%
16084990071
 
1.8%
16497926551
 
1.8%
16238296751
 
1.8%
16246469541
 
1.8%
16622313551
 
1.8%
16464889081
 
1.8%
Other values (34)34
60.7%
ValueCountFrequency (%)
16071040921
1.8%
16084990071
1.8%
16093598271
1.8%
16098872012
3.6%
16114368421
1.8%
16238295291
1.8%
16238296751
1.8%
16246469541
1.8%
16254352901
1.8%
16296353541
1.8%
ValueCountFrequency (%)
16622908591
1.8%
16622756681
1.8%
16622629611
1.8%
16622313551
1.8%
16616661431
1.8%
16612693571
1.8%
16611090651
1.8%
16610060421
1.8%
16604017471
1.8%
16589222681
1.8%

_embedded.show._links.self.href
Categorical

HIGH CORRELATION

Distinct44
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://api.tvmaze.com/shows/57032
10 
https://api.tvmaze.com/shows/47912
 
2
https://api.tvmaze.com/shows/31894
 
2
https://api.tvmaze.com/shows/51125
 
2
https://api.tvmaze.com/shows/41648
 
1
Other values (39)
39 

Length

Max length34
Median length34
Mean length33.92857143
Min length33

Characters and Unicode

Total characters1900
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)71.4%

Sample

1st rowhttps://api.tvmaze.com/shows/41648
2nd rowhttps://api.tvmaze.com/shows/7847
3rd rowhttps://api.tvmaze.com/shows/35551
4th rowhttps://api.tvmaze.com/shows/49206
5th rowhttps://api.tvmaze.com/shows/51670

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/5703210
 
17.9%
https://api.tvmaze.com/shows/479122
 
3.6%
https://api.tvmaze.com/shows/318942
 
3.6%
https://api.tvmaze.com/shows/511252
 
3.6%
https://api.tvmaze.com/shows/416481
 
1.8%
https://api.tvmaze.com/shows/615361
 
1.8%
https://api.tvmaze.com/shows/538511
 
1.8%
https://api.tvmaze.com/shows/560671
 
1.8%
https://api.tvmaze.com/shows/579451
 
1.8%
https://api.tvmaze.com/shows/608481
 
1.8%
Other values (34)34
60.7%

Length

2022-09-05T21:38:05.484712image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/5703210
 
17.9%
https://api.tvmaze.com/shows/511252
 
3.6%
https://api.tvmaze.com/shows/479122
 
3.6%
https://api.tvmaze.com/shows/318942
 
3.6%
https://api.tvmaze.com/shows/402321
 
1.8%
https://api.tvmaze.com/shows/78471
 
1.8%
https://api.tvmaze.com/shows/355511
 
1.8%
https://api.tvmaze.com/shows/492061
 
1.8%
https://api.tvmaze.com/shows/516701
 
1.8%
https://api.tvmaze.com/shows/559191
 
1.8%
Other values (34)34
60.7%

Most occurring characters

ValueCountFrequency (%)
/224
 
11.8%
s168
 
8.8%
t168
 
8.8%
h112
 
5.9%
p112
 
5.9%
a112
 
5.9%
o112
 
5.9%
.112
 
5.9%
m112
 
5.9%
e56
 
2.9%
Other values (16)612
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1232
64.8%
Other Punctuation392
 
20.6%
Decimal Number276
 
14.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s168
13.6%
t168
13.6%
h112
9.1%
p112
9.1%
a112
9.1%
o112
9.1%
m112
9.1%
e56
 
4.5%
w56
 
4.5%
c56
 
4.5%
Other values (3)168
13.6%
Decimal Number
ValueCountFrequency (%)
548
17.4%
332
11.6%
028
10.1%
227
9.8%
427
9.8%
127
9.8%
725
9.1%
624
8.7%
921
7.6%
817
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/224
57.1%
.112
28.6%
:56
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1232
64.8%
Common668
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/224
33.5%
.112
16.8%
:56
 
8.4%
548
 
7.2%
332
 
4.8%
028
 
4.2%
227
 
4.0%
427
 
4.0%
127
 
4.0%
725
 
3.7%
Other values (3)62
 
9.3%
Latin
ValueCountFrequency (%)
s168
13.6%
t168
13.6%
h112
9.1%
p112
9.1%
a112
9.1%
o112
9.1%
m112
9.1%
e56
 
4.5%
w56
 
4.5%
c56
 
4.5%
Other values (3)168
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/224
 
11.8%
s168
 
8.8%
t168
 
8.8%
h112
 
5.9%
p112
 
5.9%
a112
 
5.9%
o112
 
5.9%
.112
 
5.9%
m112
 
5.9%
e56
 
2.9%
Other values (16)612
32.2%
Distinct44
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size576.0 B
https://api.tvmaze.com/episodes/2155222
10 
https://api.tvmaze.com/episodes/1972591
 
2
https://api.tvmaze.com/episodes/2228050
 
2
https://api.tvmaze.com/episodes/1992714
 
2
https://api.tvmaze.com/episodes/1988862
 
1
Other values (39)
39 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2184
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)71.4%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/2338362
3rd rowhttps://api.tvmaze.com/episodes/2330393
4th rowhttps://api.tvmaze.com/episodes/2386129
5th rowhttps://api.tvmaze.com/episodes/1993891

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/215522210
 
17.9%
https://api.tvmaze.com/episodes/19725912
 
3.6%
https://api.tvmaze.com/episodes/22280502
 
3.6%
https://api.tvmaze.com/episodes/19927142
 
3.6%
https://api.tvmaze.com/episodes/19888621
 
1.8%
https://api.tvmaze.com/episodes/23112141
 
1.8%
https://api.tvmaze.com/episodes/21135871
 
1.8%
https://api.tvmaze.com/episodes/21183791
 
1.8%
https://api.tvmaze.com/episodes/23858501
 
1.8%
https://api.tvmaze.com/episodes/22894181
 
1.8%
Other values (34)34
60.7%

Length

2022-09-05T21:38:05.571761image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/215522210
 
17.9%
https://api.tvmaze.com/episodes/19927142
 
3.6%
https://api.tvmaze.com/episodes/19725912
 
3.6%
https://api.tvmaze.com/episodes/22280502
 
3.6%
https://api.tvmaze.com/episodes/23668401
 
1.8%
https://api.tvmaze.com/episodes/23383621
 
1.8%
https://api.tvmaze.com/episodes/23303931
 
1.8%
https://api.tvmaze.com/episodes/23861291
 
1.8%
https://api.tvmaze.com/episodes/19938911
 
1.8%
https://api.tvmaze.com/episodes/23665821
 
1.8%
Other values (34)34
60.7%

Most occurring characters

ValueCountFrequency (%)
/224
 
10.3%
t168
 
7.7%
p168
 
7.7%
s168
 
7.7%
e168
 
7.7%
a112
 
5.1%
i112
 
5.1%
.112
 
5.1%
m112
 
5.1%
o112
 
5.1%
Other values (16)728
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1400
64.1%
Other Punctuation392
 
17.9%
Decimal Number392
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t168
12.0%
p168
12.0%
s168
12.0%
e168
12.0%
a112
8.0%
i112
8.0%
m112
8.0%
o112
8.0%
h56
 
4.0%
d56
 
4.0%
Other values (3)168
12.0%
Decimal Number
ValueCountFrequency (%)
2106
27.0%
154
13.8%
539
 
9.9%
339
 
9.9%
834
 
8.7%
933
 
8.4%
733
 
8.4%
619
 
4.8%
018
 
4.6%
417
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/224
57.1%
.112
28.6%
:56
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1400
64.1%
Common784
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/224
28.6%
.112
14.3%
2106
13.5%
:56
 
7.1%
154
 
6.9%
539
 
5.0%
339
 
5.0%
834
 
4.3%
933
 
4.2%
733
 
4.2%
Other values (3)54
 
6.9%
Latin
ValueCountFrequency (%)
t168
12.0%
p168
12.0%
s168
12.0%
e168
12.0%
a112
8.0%
i112
8.0%
m112
8.0%
o112
8.0%
h56
 
4.0%
d56
 
4.0%
Other values (3)168
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/224
 
10.3%
t168
 
7.7%
p168
 
7.7%
s168
 
7.7%
e168
 
7.7%
a112
 
5.1%
i112
 
5.1%
.112
 
5.1%
m112
 
5.1%
o112
 
5.1%
Other values (16)728
33.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing51
Missing (%)91.1%
Memory size576.0 B
https://api.tvmaze.com/episodes/2338363
https://api.tvmaze.com/episodes/2330394
https://api.tvmaze.com/episodes/2373586
https://api.tvmaze.com/episodes/2376729
https://api.tvmaze.com/episodes/2343875

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2338363
2nd rowhttps://api.tvmaze.com/episodes/2330394
3rd rowhttps://api.tvmaze.com/episodes/2373586
4th rowhttps://api.tvmaze.com/episodes/2376729
5th rowhttps://api.tvmaze.com/episodes/2343875

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23383631
 
1.8%
https://api.tvmaze.com/episodes/23303941
 
1.8%
https://api.tvmaze.com/episodes/23735861
 
1.8%
https://api.tvmaze.com/episodes/23767291
 
1.8%
https://api.tvmaze.com/episodes/23438751
 
1.8%
(Missing)51
91.1%

Length

2022-09-05T21:38:05.651222image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:05.739256image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23383631
20.0%
https://api.tvmaze.com/episodes/23303941
20.0%
https://api.tvmaze.com/episodes/23735861
20.0%
https://api.tvmaze.com/episodes/23767291
20.0%
https://api.tvmaze.com/episodes/23438751
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
e15
 
7.7%
p15
 
7.7%
s15
 
7.7%
t15
 
7.7%
312
 
6.2%
o10
 
5.1%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
Other values (15)63
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e15
12.0%
p15
12.0%
s15
12.0%
t15
12.0%
o10
8.0%
a10
8.0%
i10
8.0%
m10
8.0%
d5
 
4.0%
h5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
312
34.3%
26
17.1%
74
 
11.4%
83
 
8.6%
63
 
8.6%
92
 
5.7%
42
 
5.7%
52
 
5.7%
01
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e15
12.0%
p15
12.0%
s15
12.0%
t15
12.0%
o10
8.0%
a10
8.0%
i10
8.0%
m10
8.0%
d5
 
4.0%
h5
 
4.0%
Other values (3)15
12.0%
Common
ValueCountFrequency (%)
/20
28.6%
312
17.1%
.10
14.3%
26
 
8.6%
:5
 
7.1%
74
 
5.7%
83
 
4.3%
63
 
4.3%
92
 
2.9%
42
 
2.9%
Other values (2)3
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
e15
 
7.7%
p15
 
7.7%
s15
 
7.7%
t15
 
7.7%
312
 
6.2%
o10
 
5.1%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
Other values (15)63
32.3%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct17
Distinct (%)100.0%
Missing39
Missing (%)69.6%
Memory size576.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/287/717768.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/350/877095.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/287/719058.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/329/823874.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/287/717714.jpg
 
1
Other values (12)
12 

Length

Max length73
Median length72
Mean length72.05882353
Min length72

Characters and Unicode

Total characters1225
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/717768.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/717771.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726339.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/361/903572.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/286/716829.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/287/717768.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/350/877095.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719058.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/329/823874.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/287/717714.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/404/1010040.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/285/713903.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/329/823867.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716865.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/medium_landscape/287/717647.jpg1
 
1.8%
Other values (7)7
 
12.5%
(Missing)39
69.6%

Length

2022-09-05T21:38:05.838808image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/287/717768.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/287/717647.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/287/717771.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726339.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/361/903572.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716829.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725743.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/287/717646.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716865.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/medium_landscape/350/877095.jpg1
 
5.9%
Other values (7)7
41.2%

Most occurring characters

ValueCountFrequency (%)
/119
 
9.7%
a102
 
8.3%
s85
 
6.9%
m85
 
6.9%
t85
 
6.9%
p68
 
5.6%
e68
 
5.6%
i51
 
4.2%
c51
 
4.2%
.51
 
4.2%
Other values (22)460
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter867
70.8%
Other Punctuation187
 
15.3%
Decimal Number154
 
12.6%
Connector Punctuation17
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a102
11.8%
s85
9.8%
m85
9.8%
t85
9.8%
p68
 
7.8%
e68
 
7.8%
i51
 
5.9%
c51
 
5.9%
d51
 
5.9%
l34
 
3.9%
Other values (8)187
21.6%
Decimal Number
ValueCountFrequency (%)
734
22.1%
221
13.6%
820
13.0%
115
9.7%
313
 
8.4%
013
 
8.4%
612
 
7.8%
910
 
6.5%
49
 
5.8%
57
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/119
63.6%
.51
27.3%
:17
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin867
70.8%
Common358
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a102
11.8%
s85
9.8%
m85
9.8%
t85
9.8%
p68
 
7.8%
e68
 
7.8%
i51
 
5.9%
c51
 
5.9%
d51
 
5.9%
l34
 
3.9%
Other values (8)187
21.6%
Common
ValueCountFrequency (%)
/119
33.2%
.51
14.2%
734
 
9.5%
221
 
5.9%
820
 
5.6%
_17
 
4.7%
:17
 
4.7%
115
 
4.2%
313
 
3.6%
013
 
3.6%
Other values (4)38
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/119
 
9.7%
a102
 
8.3%
s85
 
6.9%
m85
 
6.9%
t85
 
6.9%
p68
 
5.6%
e68
 
5.6%
i51
 
4.2%
c51
 
4.2%
.51
 
4.2%
Other values (22)460
37.6%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct17
Distinct (%)100.0%
Missing39
Missing (%)69.6%
Memory size576.0 B
https://static.tvmaze.com/uploads/images/original_untouched/287/717768.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/350/877095.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/287/719058.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/329/823874.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/287/717714.jpg
 
1
Other values (12)
12 

Length

Max length75
Median length74
Mean length74.05882353
Min length74

Characters and Unicode

Total characters1259
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/717768.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/717771.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726339.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/361/903572.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/716829.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/287/717768.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/350/877095.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/719058.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/329/823874.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/717714.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/404/1010040.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713903.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/329/823867.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/286/716865.jpg1
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/717647.jpg1
 
1.8%
Other values (7)7
 
12.5%
(Missing)39
69.6%

Length

2022-09-05T21:38:05.938357image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/287/717768.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/287/717647.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/287/717771.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726339.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/361/903572.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/286/716829.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/725743.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/287/717646.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/286/716865.jpg1
 
5.9%
https://static.tvmaze.com/uploads/images/original_untouched/350/877095.jpg1
 
5.9%
Other values (7)7
41.2%

Most occurring characters

ValueCountFrequency (%)
/119
 
9.5%
t102
 
8.1%
a85
 
6.8%
s68
 
5.4%
o68
 
5.4%
i68
 
5.4%
m51
 
4.1%
u51
 
4.1%
e51
 
4.1%
g51
 
4.1%
Other values (23)545
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter901
71.6%
Other Punctuation187
 
14.9%
Decimal Number154
 
12.2%
Connector Punctuation17
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t102
 
11.3%
a85
 
9.4%
s68
 
7.5%
o68
 
7.5%
i68
 
7.5%
m51
 
5.7%
u51
 
5.7%
e51
 
5.7%
g51
 
5.7%
c51
 
5.7%
Other values (9)255
28.3%
Decimal Number
ValueCountFrequency (%)
734
22.1%
221
13.6%
820
13.0%
115
9.7%
313
 
8.4%
013
 
8.4%
612
 
7.8%
910
 
6.5%
49
 
5.8%
57
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/119
63.6%
.51
27.3%
:17
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin901
71.6%
Common358
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t102
 
11.3%
a85
 
9.4%
s68
 
7.5%
o68
 
7.5%
i68
 
7.5%
m51
 
5.7%
u51
 
5.7%
e51
 
5.7%
g51
 
5.7%
c51
 
5.7%
Other values (9)255
28.3%
Common
ValueCountFrequency (%)
/119
33.2%
.51
14.2%
734
 
9.5%
221
 
5.9%
820
 
5.6%
_17
 
4.7%
:17
 
4.7%
115
 
4.2%
313
 
3.6%
013
 
3.6%
Other values (4)38
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1259
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/119
 
9.5%
t102
 
8.1%
a85
 
6.8%
s68
 
5.4%
o68
 
5.4%
i68
 
5.4%
m51
 
4.1%
u51
 
4.1%
e51
 
4.1%
g51
 
4.1%
Other values (23)545
43.3%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing51
Missing (%)91.1%
Memory size576.0 B
263.0
76.0
236.0
91.0
85.0

Length

Max length5
Median length4
Mean length4.4
Min length4

Characters and Unicode

Total characters22
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row263.0
2nd row76.0
3rd row236.0
4th row91.0
5th row85.0

Common Values

ValueCountFrequency (%)
263.01
 
1.8%
76.01
 
1.8%
236.01
 
1.8%
91.01
 
1.8%
85.01
 
1.8%
(Missing)51
91.1%

Length

2022-09-05T21:38:06.024546image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:06.115312image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
263.01
20.0%
76.01
20.0%
236.01
20.0%
91.01
20.0%
85.01
20.0%

Most occurring characters

ValueCountFrequency (%)
.5
22.7%
05
22.7%
63
13.6%
22
 
9.1%
32
 
9.1%
71
 
4.5%
91
 
4.5%
11
 
4.5%
81
 
4.5%
51
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number17
77.3%
Other Punctuation5
 
22.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
05
29.4%
63
17.6%
22
 
11.8%
32
 
11.8%
71
 
5.9%
91
 
5.9%
11
 
5.9%
81
 
5.9%
51
 
5.9%
Other Punctuation
ValueCountFrequency (%)
.5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.5
22.7%
05
22.7%
63
13.6%
22
 
9.1%
32
 
9.1%
71
 
4.5%
91
 
4.5%
11
 
4.5%
81
 
4.5%
51
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.5
22.7%
05
22.7%
63
13.6%
22
 
9.1%
32
 
9.1%
71
 
4.5%
91
 
4.5%
11
 
4.5%
81
 
4.5%
51
 
4.5%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing51
Missing (%)91.1%
Memory size576.0 B
TV Asahi
TV Tokyo
Oprah Winfrey Network
NRK1
PBS

Length

Max length21
Median length8
Mean length8.8
Min length3

Characters and Unicode

Total characters44
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowTV Asahi
2nd rowTV Tokyo
3rd rowOprah Winfrey Network
4th rowNRK1
5th rowPBS

Common Values

ValueCountFrequency (%)
TV Asahi1
 
1.8%
TV Tokyo1
 
1.8%
Oprah Winfrey Network1
 
1.8%
NRK11
 
1.8%
PBS1
 
1.8%
(Missing)51
91.1%

Length

2022-09-05T21:38:06.205363image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:06.300874image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
tv2
22.2%
asahi1
11.1%
tokyo1
11.1%
oprah1
11.1%
winfrey1
11.1%
network1
11.1%
nrk11
11.1%
pbs1
11.1%

Most occurring characters

ValueCountFrequency (%)
4
 
9.1%
T3
 
6.8%
o3
 
6.8%
r3
 
6.8%
h2
 
4.5%
i2
 
4.5%
k2
 
4.5%
y2
 
4.5%
V2
 
4.5%
a2
 
4.5%
Other values (17)19
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter24
54.5%
Uppercase Letter15
34.1%
Space Separator4
 
9.1%
Decimal Number1
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
12.5%
r3
12.5%
h2
8.3%
i2
8.3%
k2
8.3%
y2
8.3%
a2
8.3%
e2
8.3%
s1
 
4.2%
w1
 
4.2%
Other values (4)4
16.7%
Uppercase Letter
ValueCountFrequency (%)
T3
20.0%
V2
13.3%
N2
13.3%
B1
 
6.7%
P1
 
6.7%
K1
 
6.7%
R1
 
6.7%
W1
 
6.7%
O1
 
6.7%
A1
 
6.7%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin39
88.6%
Common5
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
T3
 
7.7%
o3
 
7.7%
r3
 
7.7%
h2
 
5.1%
i2
 
5.1%
k2
 
5.1%
y2
 
5.1%
V2
 
5.1%
a2
 
5.1%
e2
 
5.1%
Other values (15)16
41.0%
Common
ValueCountFrequency (%)
4
80.0%
11
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII44
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
 
9.1%
T3
 
6.8%
o3
 
6.8%
r3
 
6.8%
h2
 
4.5%
i2
 
4.5%
k2
 
4.5%
y2
 
4.5%
V2
 
4.5%
a2
 
4.5%
Other values (17)19
43.2%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)60.0%
Missing51
Missing (%)91.1%
Memory size576.0 B
Japan
United States
Norway

Length

Max length13
Median length6
Mean length8.4
Min length5

Characters and Unicode

Total characters42
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st rowJapan
2nd rowJapan
3rd rowUnited States
4th rowNorway
5th rowUnited States

Common Values

ValueCountFrequency (%)
Japan2
 
3.6%
United States2
 
3.6%
Norway1
 
1.8%
(Missing)51
91.1%

Length

2022-09-05T21:38:06.390816image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:06.478772image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
japan2
28.6%
united2
28.6%
states2
28.6%
norway1
14.3%

Most occurring characters

ValueCountFrequency (%)
a7
16.7%
t6
14.3%
n4
9.5%
e4
9.5%
J2
 
4.8%
s2
 
4.8%
S2
 
4.8%
2
 
4.8%
d2
 
4.8%
i2
 
4.8%
Other values (7)9
21.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter33
78.6%
Uppercase Letter7
 
16.7%
Space Separator2
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a7
21.2%
t6
18.2%
n4
12.1%
e4
12.1%
s2
 
6.1%
d2
 
6.1%
i2
 
6.1%
p2
 
6.1%
o1
 
3.0%
r1
 
3.0%
Other values (2)2
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
J2
28.6%
S2
28.6%
U2
28.6%
N1
14.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin40
95.2%
Common2
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a7
17.5%
t6
15.0%
n4
10.0%
e4
10.0%
J2
 
5.0%
s2
 
5.0%
S2
 
5.0%
d2
 
5.0%
i2
 
5.0%
U2
 
5.0%
Other values (6)7
17.5%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a7
16.7%
t6
14.3%
n4
9.5%
e4
9.5%
J2
 
4.8%
s2
 
4.8%
S2
 
4.8%
2
 
4.8%
d2
 
4.8%
i2
 
4.8%
Other values (7)9
21.4%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)60.0%
Missing51
Missing (%)91.1%
Memory size576.0 B
JP
US
NO

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters10
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st rowJP
2nd rowJP
3rd rowUS
4th rowNO
5th rowUS

Common Values

ValueCountFrequency (%)
JP2
 
3.6%
US2
 
3.6%
NO1
 
1.8%
(Missing)51
91.1%

Length

2022-09-05T21:38:06.554516image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:06.633823image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
jp2
40.0%
us2
40.0%
no1
20.0%

Most occurring characters

ValueCountFrequency (%)
J2
20.0%
P2
20.0%
U2
20.0%
S2
20.0%
N1
10.0%
O1
10.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter10
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
J2
20.0%
P2
20.0%
U2
20.0%
S2
20.0%
N1
10.0%
O1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
J2
20.0%
P2
20.0%
U2
20.0%
S2
20.0%
N1
10.0%
O1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
J2
20.0%
P2
20.0%
U2
20.0%
S2
20.0%
N1
10.0%
O1
10.0%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)60.0%
Missing51
Missing (%)91.1%
Memory size576.0 B
Asia/Tokyo
America/New_York
Europe/Oslo

Length

Max length16
Median length11
Mean length12.6
Min length10

Characters and Unicode

Total characters63
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st rowAsia/Tokyo
2nd rowAsia/Tokyo
3rd rowAmerica/New_York
4th rowEurope/Oslo
5th rowAmerica/New_York

Common Values

ValueCountFrequency (%)
Asia/Tokyo2
 
3.6%
America/New_York2
 
3.6%
Europe/Oslo1
 
1.8%
(Missing)51
91.1%

Length

2022-09-05T21:38:06.713974image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:38:06.803145image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/tokyo2
40.0%
america/new_york2
40.0%
europe/oslo1
20.0%

Most occurring characters

ValueCountFrequency (%)
o8
12.7%
r5
 
7.9%
e5
 
7.9%
/5
 
7.9%
k4
 
6.3%
A4
 
6.3%
a4
 
6.3%
i4
 
6.3%
s3
 
4.8%
T2
 
3.2%
Other values (12)19
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter44
69.8%
Uppercase Letter12
 
19.0%
Other Punctuation5
 
7.9%
Connector Punctuation2
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o8
18.2%
r5
11.4%
e5
11.4%
k4
9.1%
a4
9.1%
i4
9.1%
s3
 
6.8%
y2
 
4.5%
m2
 
4.5%
c2
 
4.5%
Other values (4)5
11.4%
Uppercase Letter
ValueCountFrequency (%)
A4
33.3%
T2
16.7%
N2
16.7%
Y2
16.7%
E1
 
8.3%
O1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
/5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin56
88.9%
Common7
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o8
14.3%
r5
 
8.9%
e5
 
8.9%
k4
 
7.1%
A4
 
7.1%
a4
 
7.1%
i4
 
7.1%
s3
 
5.4%
T2
 
3.6%
y2
 
3.6%
Other values (10)15
26.8%
Common
ValueCountFrequency (%)
/5
71.4%
_2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o8
12.7%
r5
 
7.9%
e5
 
7.9%
/5
 
7.9%
k4
 
6.3%
A4
 
6.3%
a4
 
6.3%
i4
 
6.3%
s3
 
4.8%
T2
 
3.2%
Other values (12)19
30.2%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing56
Missing (%)100.0%
Memory size576.0 B

Interactions

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2022-09-05T21:37:55.314652image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:38:06.895564image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:38:07.134884image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:38:07.362123image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:38:07.645998image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:37:56.454339image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:37:57.094921image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:37:57.540307image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show._links.nextepisode.hrefimage.mediumimage.original_embedded.show.image_embedded.show.webChannel.country_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel
01979826https://www.tvmaze.com/episodes/1979826/sim-for-you-4x18-chanyeols-episode-18Chanyeol's Episode 18418regular2020-12-0506:002020-12-04T21:00:00+00:0016.0NaN<p><b>#DangerQuest #AbleToFly(?) #EntranceOfAWindSkill</b></p>NaNhttps://api.tvmaze.com/episodes/197982641648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25Nonehttps://www.vlive.tv/video/121637[Monday, Wednesday, Friday]NaN29NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNoneNaN361541.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpghttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1608499007https://api.tvmaze.com/shows/41648https://api.tvmaze.com/episodes/1988862NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11968112https://www.tvmaze.com/episodes/1968112/po-sezonu-videodajdzest-seasonvar-6x49-vypusk-303Выпуск 303649regular2020-12-052020-12-05T00:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19681127847https://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvarПо сезону. Видеодайджест SeasonvarTalk ShowRussian[]Running9.08.02015-02-13Nonehttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html[Friday]NaN63NaN56.0SeasonvarRussian FederationRUAsia/KamchatkaNoneNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/294/735323.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/735323.jpg<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>1662290859https://api.tvmaze.com/shows/7847https://api.tvmaze.com/episodes/2338362https://api.tvmaze.com/episodes/2338363NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21980956https://www.tvmaze.com/episodes/1980956/soul-land-7x03-di133ji第133集73regular2020-12-0510:002020-12-05T02:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198095635551https://www.tvmaze.com/shows/35551/soul-landSoul LandAnimationChinese[Action, Adventure, Anime, Fantasy]Running20.020.02018-01-13Nonehttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html10:00[Saturday]7.791NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN342329.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/150/375304.jpghttps://static.tvmaze.com/uploads/images/original_untouched/150/375304.jpg<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>1652939782https://api.tvmaze.com/shows/35551https://api.tvmaze.com/episodes/2330393https://api.tvmaze.com/episodes/2330394NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
32386104https://www.tvmaze.com/episodes/2386104/xian-feng-jian-yu-lu-1x45-episode-45Episode 45145regular2020-12-0510:002020-12-05T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/238610449206https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-luXian Feng Jian Yu LuAnimationChinese[Action, Anime, Fantasy, Supernatural]Running8.07.02020-07-11Nonehttps://v.qq.com/detail/m/mzc00200hc38s5x.html10:00[Wednesday, Saturday]NaN62NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN386423.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpghttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>1662275668https://api.tvmaze.com/shows/49206https://api.tvmaze.com/episodes/2386129NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
41962056https://www.tvmaze.com/episodes/1962056/heaven-officials-blessing-1x07-scorpion-tailed-snake-shadowScorpion-Tailed Snake Shadow17regular2020-12-0511:002020-12-05T03:00:00+00:0025.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196205651670https://www.tvmaze.com/shows/51670/heaven-officials-blessingHeaven Official's BlessingAnimationChinese[Drama, Anime, Fantasy, Romance]Running25.025.02020-10-31Nonehttps://www.bilibili.com/tgcf11:00[Saturday]7.344NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNoneNaN388672.0tt13375866https://static.tvmaze.com/uploads/images/medium_portrait/414/1036502.jpghttps://static.tvmaze.com/uploads/images/original_untouched/414/1036502.jpg<p>"Have you heard? The rubbish Heaven Official is having an affair with the ghost realm's number one bigshot!"</p><p>Eight hundred years ago, Xie Lian was the Crown Prince of the Xian Le kingdom; one who was beloved by his citizens and the darling of the world. Unsurprisingly, he ascended to the Heavens at a very young age. Now, eight hundred years later, Xie Lian ascends to the Heavens for the third time as the laughing stock of all three realms. On his first task as a god, he meets a mysterious demon who rules the ghosts and terrifies the Heavens... yet unbeknownst to Xie Lian, this demon king has been paying attention to him for a very, very long time.</p>1656761777https://api.tvmaze.com/shows/51670https://api.tvmaze.com/episodes/1993891NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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511967067https://www.tvmaze.com/episodes/1967067/maskorama-1x05-episode-5Episode 515regular2020-12-0519:502020-12-05T18:50:00+00:0091.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196706751314https://www.tvmaze.com/shows/51314/maskoramaMaskoramaRealityNorwegian[Music]Running90.088.02020-11-07Nonehttps://tv.nrk.no/serie/maskorama19:50[Saturday]NaN22NaN238.0NRK TVNorwayNOEurope/OsloNoneNoneNaN391528.0tt13510734https://static.tvmaze.com/uploads/images/medium_portrait/370/926987.jpghttps://static.tvmaze.com/uploads/images/original_untouched/370/926987.jpg<p>Based on the international hit "The Masked Singer", in <b>Maskorama </b>eight elebrities will face off against one another with a twist: each singer is using masks and costumes, the judges panel will have to guess which celebrity is behind the mask.</p>1640454812https://api.tvmaze.com/shows/51314https://api.tvmaze.com/episodes/2207405NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719058.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/719058.jpgNaNNaN91.0NRK1NorwayNOEurope/OsloNaNNaN
521969219https://www.tvmaze.com/episodes/1969219/eides-spraksjov-6x03-songar-fra-nyheiteneSongar frå nyheitene63regular2020-12-0521:552020-12-05T20:55:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196921951631https://www.tvmaze.com/shows/51631/eides-spraksjovEides språksjovTalk ShowNorwegian[Comedy]RunningNaN43.02017-01-11Nonehttps://tv.nrk.no/serie/eides-spraaksjov[Saturday]NaN4NaN238.0NRK TVNorwayNOEurope/OsloNoneNoneNaN322906.0tt8851444https://static.tvmaze.com/uploads/images/medium_portrait/280/701389.jpghttps://static.tvmaze.com/uploads/images/original_untouched/280/701389.jpg<p>Entertainment from here to the moon when Linda Eide and guests pay tribute and joke with language.</p>1650016918https://api.tvmaze.com/shows/51631https://api.tvmaze.com/episodes/2297850NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
531977712https://www.tvmaze.com/episodes/1977712/onyx-equinox-1x03-thicker-than-waterThicker Than Water13regular2020-12-0516:002020-12-05T21:00:00+00:0024.0NaN<p>Izel heads to Ox Te'Tuun to retrieve an artifact containing the map to the gates. There, he meets twin Ulama ballplayers, as well as mysterious figure from his past. </p>8.0https://api.tvmaze.com/episodes/197771248922https://www.tvmaze.com/shows/48922/onyx-equinoxOnyx EquinoxAnimationEnglish[Action, Adventure, Fantasy]Ended24.024.02020-11-212020-12-26https://www.crunchyroll.com/onyx-equinox16:00[Saturday]5.046NaN20.0CrunchyrollNaNNaNNaNNoneNoneNaN377625.0tt12605636https://static.tvmaze.com/uploads/images/medium_portrait/263/658930.jpghttps://static.tvmaze.com/uploads/images/original_untouched/263/658930.jpg<p>A young Aztec boy is saved from death by the gods and chosen to act as ‘humanity's champion,' forced to discard his apathy toward his fellow man and prove humanity's potential in a fight that spans across fantastical-yet-authentic Mesoamerican cultures.</p>1609359827https://api.tvmaze.com/shows/48922https://api.tvmaze.com/episodes/1990352NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
542153702https://www.tvmaze.com/episodes/2153702/field-trip-with-curtis-stone-2x06-hawaiiHawai'i26regular2020-12-0519:302020-12-06T00:30:00+00:0030.0NaN<p>Curtis dives with competitive spearfisherman Justin Lee and tours the Berkshire pig farm run by his brother, Brandon. Later, Curtis is introduced to the tradition of Paniolos - Hawaiian cowboys.</p>NaNhttps://api.tvmaze.com/episodes/215370244334https://www.tvmaze.com/shows/44334/field-trip-with-curtis-stoneField Trip with Curtis StoneDocumentaryEnglish[Food, Travel]Running30.030.02019-10-07Nonehttps://fieldtripwithcurtisstone.com/19:30[Saturday]NaN22NaN347.0PeacockUnited StatesUSAmerica/New_Yorkhttps://www.peacocktv.com/NoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/301/754854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/301/754854.jpg<p>In <b>Field Trip with Curtis Stone</b>, chef Curtis Stone embarks on a global culinary journey to explore the spirit and passion of the destinations which inform the menu at Maude, his Michelin-starred restaurant in Beverly Hills. Curtis and friends travel to Australia, Italy, Spain and California, hunting pheasants, herding cattle and diving for pearls as they track the delicacies Curtis serves in his restaurant to their source.</p>1629660646https://api.tvmaze.com/shows/44334https://api.tvmaze.com/episodes/2153699NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/350/877095.jpghttps://static.tvmaze.com/uploads/images/original_untouched/350/877095.jpgNaNNaN85.0PBSUnited StatesUSAmerica/New_YorkNaNNaN
551984186https://www.tvmaze.com/episodes/1984186/ufc-fight-night-2020-12-05-ufc-on-espn-19-hermansson-vs-vettoriUFC on ESPN 19: Hermansson vs. Vettori202029regular2020-12-0522:002020-12-06T03:00:00+00:00293.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19841861596https://www.tvmaze.com/shows/1596/ufc-fight-nightUFC Fight NightSportsEnglish[]Running120.0194.02005-08-06Nonehttp://www.ufc.com/22:00[Saturday]7.795NaN265.0ESPN+United StatesUSAmerica/New_YorkNoneNone15090.0NaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/293/734642.jpghttps://static.tvmaze.com/uploads/images/original_untouched/293/734642.jpg<p><b>UFC Fight Night</b> is a part of the Ultimate Fighting Championship (UFC) which is the largest mixed martial arts promotion company in the world featuring most of the top-ranked fighters in the sport. Based in the United States, the UFC produces events worldwide. The organization showcases nine weight divisions and abides by the Unified Rules of Mixed Martial Arts. The UFC has held over 300 events to date. Dana White serves as the president of the UFC while brothers Frank and Lorenzo Fertitta control the UFC's parent company, Zuffa, LLC. The first UFC event was held on November 12, 1993 at the McNichols Sports Arena in Denver, Colorado. The purpose of the early UFC competitions was to identify the most effective martial art in a real fight between competitors of different fighting disciplines, including boxing, Brazilian jiu-jitsu, Sambo, wrestling, Muay Thai, karate, judo, and other styles. In subsequent competitions, fighters began adopting effective techniques from more than one discipline, which indirectly helped create an entirely separate style of fighting known as present-day mixed martial arts.</p>1661666143https://api.tvmaze.com/shows/1596https://api.tvmaze.com/episodes/2343874https://api.tvmaze.com/episodes/2343875https://static.tvmaze.com/uploads/images/medium_landscape/288/721043.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721043.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaN